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CAREER: Investigating Host Response in the Pathogenesis of FV3 (Ranavirus sp) in Wood Frogs, Rana sylvatica (Lithobates sylvaticus)
|
NSF
|
05/01/2024
|
06/30/2026
| 1,145,610 | 1,016,399 |
{'Value': 'Continuing Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Joanna Shisler', 'PO_EMAI': 'jshisler@nsf.gov', 'PO_PHON': '7032925368'}
|
Amphibians worldwide are experiencing unprecedented population losses, with some scientists wondering if the earth is at the beginning of the 6th mass extinction. Infectious diseases are a significant threat to amphibian survival. Ranavirosis is caused by Frog Virus 3 (FV3), and causes disease and death in wild and captive amphibians worldwide. FV3 infections of wild tadpoles often result in die-offs of populations reaching close to 100% mortality, a rate that significantly impacts the stability of future wild frog populations. If RV3 moves into captive amphibian populations, it jeopardized breeding programs of endangered species. There must be an understanding of FV3’s pathogenesis (how infection develops in the host) to mitigate ranavirosis. Pathogenesis of FV3 is influenced by many things including: the amphibian’s immune response to infection, and environmental factors linked to the amphibian’s life history, such as sharing habitat with species that serve as virus reservoirs (carriers) or living under unfavorable conditions. This CAREER award will investigate the pathogenesis of FV3 in wood frogs, a native frog species severely affected by outbreaks of ranavirosis. It focuses on the frog’s response to infection, the effects of environment (temperature changes), stress, and presence carriers on infection outcomes. This research funds basic research whose findings will inform decisions in management of wild and captive amphibians. Training of graduate students in this research area will also prepare the next generation of STEM researchers for the workforce. In addition, there are outreach activities to inform the general public about FV3 and frogs to help educate people about current threats to wildlife.<br/><br/><br/>TECHNICAL OVERVIEW<br/><br/>It is theorized that FV3 introduction into a naïve population of wood frogs (Rana sylvatica) will result in local extinction within 5 years. The investigator’s central hypothesis is that the life history (biology and ecology) of the host, its immune response, and the environment it inhabits will determine the outcome of FV3 infection. The PIs previous work found that survivors of sublethal FV3 infections (like green frogs, Rana clamitans) may become long-term carriers of the virus. Thus, environments with green frogs may be associated with ranavirosis tadpole mortalities in wild populations. The proposed research will determine the pathogenesis of infection in tadpoles, disentangle the relationship between (putatively) resistant species (green frogs) and highly susceptible ones (wood frogs); determine if long-term carriers develop when individuals survive infection; characterize the cellular and/or humoral immune response to FV3 infection in adult wood frogs; and determine whether subclinical disease provides protection to re-infection. The work will involve experimental infections of wild-caught, lab-raised, tadpoles and adults, determination of LD50 doses, histopathological examination of affected animals, application of immunohistochemical and molecular labeling (in situ hybridization) techniques to detect target cells/tissues, hematological evaluation of cellular and humoral immune responses, and determination of the effect of corticosteroids on those responses.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/07/2024
|
08/07/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2438615
|
{'FirstName': 'Maria', 'LastName': 'Forzan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Maria Forzan', 'EmailAddress': 'maria.forzan@liu.edu', 'NSF_ID': '000761905', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Wyoming', 'CityName': 'LARAMIE', 'ZipCode': '820712000', 'PhoneNumber': '3077665320', 'StreetAddress': '1000 E UNIVERSITY AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wyoming', 'StateCode': 'WY', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'WY00', 'ORG_UEI_NUM': 'FDR5YF2K32X5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WYOMING', 'ORG_PRNT_UEI_NUM': 'FDR5YF2K32X5'}
|
{'Name': 'University of Wyoming', 'CityName': 'LARAMIE', 'StateCode': 'WY', 'ZipCode': '820712000', 'StreetAddress': '1000 E UNIVERSITY AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wyoming', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'WY00'}
|
{'Code': '765600', 'Text': 'Symbiosis Infection & Immunity'}
|
['2021~585776', '2022~430623']
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438615.xml'}
|
An Interdisciplinary Workshop Reducing Uncertainty in Soluble aerosol Trace Element Deposition (RUSTED); Goa, India; November 10-14, 2024
|
NSF
|
08/15/2024
|
07/31/2025
| 20,000 | 20,000 |
{'Value': 'Standard Grant'}
|
{'Code': '06020100', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'AGS', 'LongName': 'Div Atmospheric & Geospace Sciences'}}
|
{'SignBlockName': 'Sylvia Edgerton', 'PO_EMAI': 'sedgerto@nsf.gov', 'PO_PHON': '7032928522'}
|
This project supports travel for early career scientists to attend the conference: “Reducing Uncertainty in Soluble aerosol Trace Element Deposition (RUSTED).” This meeting will bring together an international group of scientific experts from the fields of ocean biogeochemistry, atmospheric chemistry, and modeling to focus on compiling trace element solubility data and to discuss ways to improve the handling of soluble iron in Earth System models. Accurate identification and description of iron biogeochemical processes at the atmosphere-ocean boundary are crucial for confident projections of human-induced effects on the carbon cycle and climate, as well as understanding atmospheric nutrient deposition impacts on phytoplankton.<br/><br/>The RUSTED Early Career Researcher Workshop is scheduled to take place from November 10-14, 2024, at CSIR - National Institute of Oceanography located in Goa, India. The workshop builds upon the foundation laid by two preceding workshops, which focused on enhancing the comprehension of iron's influence on ocean biogeochemistry, carbon sequestration, and climate dynamics. The meeting includes a focus on critical questions about iron biogeochemical cycling in the Earth System. Participants will be engaged to explore what simultaneous information would be needed to improve model predictions to better represent climate forcing and feedbacks and what steps must be taken to acquire such information, gain insight, and answer the most critical questions. Ocean biogeochemical models have progressed in treating different dissolved forms, but kinetic descriptions of processes affecting iron solubility after deposition remain rudimentary. <br/><br/>One third of the invited researchers will be early career scientists (PhD students, postdoctoral researchers, and young research scientists who received their PhD after 2018). The workshop will facilitate interactive discussions among researchers at various stages of their careers working on different aspects of iron biogeochemistry. This workshop is also sponsored by the Scientific Committee on Oceanic Research (SCOR), a non-profit, non-governmental organization that works to advance international oceanographic research.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/06/2024
|
08/06/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2438642
|
[{'FirstName': 'Nicholas', 'LastName': 'Meskhidze', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nicholas Meskhidze', 'EmailAddress': 'nmeskhidze@ncsu.edu', 'NSF_ID': '000260369', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Douglas', 'LastName': 'Hamilton', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Douglas S Hamilton', 'EmailAddress': 'dshamil3@ncsu.edu', 'NSF_ID': '0000A00CY', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'North Carolina State University', 'CityName': 'RALEIGH', 'ZipCode': '276950001', 'PhoneNumber': '9195152444', 'StreetAddress': '2601 WOLF VILLAGE WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'NC02', 'ORG_UEI_NUM': 'U3NVH931QJJ3', 'ORG_LGL_BUS_NAME': 'NORTH CAROLINA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'U3NVH931QJJ3'}
|
{'Name': 'North Carolina State University', 'CityName': 'RALEIGH', 'StateCode': 'NC', 'ZipCode': '276950001', 'StreetAddress': '2601 WOLF VILLAGE WAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'NC02'}
|
{'Code': '152400', 'Text': 'Atmospheric Chemistry'}
|
2024~20000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438642.xml'}
|
Travel: Student Travel Grant for the International Conference on Security and Privacy in Cyber-Physical Systems and Smart Vehicles (EAI SmartSP 2024)
|
NSF
|
11/01/2024
|
04/30/2025
| 8,000 | 8,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Dan Cosley', 'PO_EMAI': 'dcosley@nsf.gov', 'PO_PHON': '7032928832'}
|
This award provides funding support for students to attend the Second EAI International Conference on Security and Privacy in Cyber-Physical Systems and Smart Vehicles (SmartSP 2024), to be held in New Orleans, Louisiana. Recent decades have witnessed an extraordinary growth in cyber-physical systems (CPS) such as self-driving vehicles, robotic devices, and drones. SmartSP is a global forum for researchers and developers from academia, industry, and government to present and discuss emerging ideas and trends in security and privacy issues in this exciting area with a particular focus on smart vehicles, smart transportation, and corresponding security challenges. The conference is particularly relevant for students and early-career researchers seeking to expand their knowledge, develop essential career skills, and engage with leading experts in the field. Together, the funding will help the intellectual and professional development of the students who attend and the SmartSP community as a whole.<br/><br/>The funding will help cover travel expenses for up to 8 U.S.-based student attendees. Selection of student attendees will be based on a range of criteria, including academic achievement, research experience, and interest in CPS, smart vehicles, and security challenges. Preference will be given to students who have conducted research in these areas and who have demonstrated a commitment to advancing the field through their academic and professional activities. Students attending the EAI SmartSP 2024 conference will be involved in a range of activities, including attending technical sessions, presenting their research, and participating in panel discussions and networking events. These activities will provide opportunities for students to meet with leading experts in the field, engage in discussions about emerging trends and technologies, and explore potential career opportunities.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/22/2024
|
08/22/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2438643
|
{'FirstName': 'Yazhou', 'LastName': 'Tu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yazhou Tu', 'EmailAddress': 'yzt0065@auburn.edu', 'NSF_ID': '000872974', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Auburn University', 'CityName': 'AUBURN', 'ZipCode': '368490001', 'PhoneNumber': '3348444438', 'StreetAddress': '321-A INGRAM HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Alabama', 'StateCode': 'AL', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'AL03', 'ORG_UEI_NUM': 'DMQNDJDHTDG4', 'ORG_LGL_BUS_NAME': 'AUBURN UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'DMQNDJDHTDG4'}
|
{'Name': 'Auburn University', 'CityName': 'AUBURN', 'StateCode': 'AL', 'ZipCode': '368490001', 'StreetAddress': '321-A INGRAM HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Alabama', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'AL03'}
|
{'Code': '806000', 'Text': 'Secure &Trustworthy Cyberspace'}
|
2024~8000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438643.xml'}
|
Conference: The PUI Research Nexus: Faculty, staff, and administrators raise awareness, assess systemic barriers, and prepare to act in support of the research enterprise
|
NSF
|
04/01/2024
|
02/28/2025
| 100,000 | 100,000 |
{'Value': 'Standard Grant'}
|
{'Code': '01060000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OIA', 'LongName': 'OIA-Office of Integrative Activities'}}
|
{'SignBlockName': 'Kimberly Littlefield', 'PO_EMAI': 'klittlef@nsf.gov', 'PO_PHON': '7032924632'}
|
In this project, regional inter-institutional workshops will be offered to teams of research administrators, institutional leaders, and faculty from Primarily Undergraduate Institutions (PUIs) to catalyze the identification of common barriers that limit research activity and the collaborative development of solutions to overcome these barriers to grow capability and capacity. Increasing the research capacity and infrastructure at PUIs will promote faculty and student engagement in research activities and broaden participation in the nation’s research enterprise.<br/><br/>As a first step towards creating a collaborative and transformative PUI research capacity and capability building model that overcomes common research support structural barriers, this project will offer one-day workshops in the Midwest, Northwest, and Southeast regions of the United States. Teams of research administrators, faculty, and institutional leaders will gather to identify challenges, build regional support networks, and create shared resources that increase the success of their institutional research enterprise. The resulting suite of best practices will be the foundation of a research toolkit that can be implemented broadly in PUIs across the nation.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/27/2024
|
08/27/2024
|
None
|
Grant
|
47.083
|
1
|
4900
|
4900
|
2438685
|
{'FirstName': 'Erica', 'LastName': 'Kennedy', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Erica Kennedy', 'EmailAddress': 'Erica.Kennedy@usm.edu', 'NSF_ID': '000782917', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Southern Mississippi', 'CityName': 'HATTIESBURG', 'ZipCode': '394060001', 'PhoneNumber': '6012664119', 'StreetAddress': '118 COLLEGE DRIVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Mississippi', 'StateCode': 'MS', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MS04', 'ORG_UEI_NUM': 'M1K8LJAET5R1', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF SOUTHERN MISSISSIPPI', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Southern Mississippi', 'CityName': 'HATTIESBURG', 'StateCode': 'MS', 'ZipCode': '394060001', 'StreetAddress': '118 COLLEGE DRIVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Mississippi', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MS04'}
|
{'Code': '221Y00', 'Text': 'GRANTED'}
|
2023~100000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438685.xml'}
|
EAGER: HCC: Exploring Human Factors: Is a Teleoperated Robotics Framework Feasible for Persons who are Visually Impaired?
|
NSF
|
10/01/2024
|
09/30/2025
| 140,758 | 140,758 |
{'Value': 'Standard Grant'}
|
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
|
{'SignBlockName': 'Cindy Bethel', 'PO_EMAI': 'cbethel@nsf.gov', 'PO_PHON': '7032924420'}
|
Visual impairment (blind or low vision) affects over seven million people in the United States. Their daily activities are more challenging. They also have a harder time finding and keeping jobs. One major challenge for people who are blind or have low vision is getting around in unfamiliar places. Such places can change often and be unpredictable. Employers worry about hiring people with visual impairments because of potential legal issues. New developments in robotics could help people with visual impairments. This project will figure out if people with visual impairments can use robots at work. Telerobots have a human user who drives the robot, while the robot supplies sensor data. The research team will do surveys, interviews, and studies with individuals who have visual impairments. This will help to identify problems with training people with visual impairments to use telerobots. The goal is to help blind and low vision users to be independent and hold technology jobs. <br/> <br/>The project has several aims. The research team is partnering with Austin Lighthouse (ALH). ALH employs hundreds of legally blind and low vision warehouse workers. Surveys will clarify the challenges people with visual impairments have getting or keeping jobs. We will interview employees at ALH to understand their needs and if they want to use the technology. Another aim is to design and do pilot studies that simulate telerobotic tasks. This will help us learn how to train blind and low vision individuals to use telerobots. It will also help make the system easier and more intuitive to use. The team will test different user interfaces to develop a telerobotic training prototype. The team will confirm the survey and interview results through telerobot training sessions. These results could give insights into how blind and low vision people do physical tasks.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/30/2024
|
07/30/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2438700
|
[{'FirstName': 'Nicholas', 'LastName': 'Gans', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nicholas Gans', 'EmailAddress': 'nicholas.gans@uta.edu', 'NSF_ID': '000564957', 'StartDate': '07/30/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Fillia', 'LastName': 'Makedon', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Fillia S Makedon', 'EmailAddress': 'makedon@cse.uta.edu', 'NSF_ID': '000191699', 'StartDate': '07/30/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'University of Texas at Arlington', 'CityName': 'ARLINGTON', 'ZipCode': '760199800', 'PhoneNumber': '8172722105', 'StreetAddress': '701 S NEDDERMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'TX25', 'ORG_UEI_NUM': 'LMLUKUPJJ9N3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TEXAS AT ARLINGTON', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Texas at Arlington', 'CityName': 'ARLINGTON', 'StateCode': 'TX', 'ZipCode': '760199800', 'StreetAddress': '701 S NEDDERMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'TX25'}
|
{'Code': '736700', 'Text': 'HCC-Human-Centered Computing'}
|
2024~140758
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438700.xml'}
|
HCC: RAPID: Understanding Imagined Futures around Generative AI Use in Higher Education
|
NSF
|
10/01/2024
|
09/30/2025
| 131,176 | 131,176 |
{'Value': 'Standard Grant'}
|
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
|
{'SignBlockName': 'Dan Cosley', 'PO_EMAI': 'dcosley@nsf.gov', 'PO_PHON': '7032928832'}
|
Computers can now generate text that closely resembles human writing in a wide variety of domains, from essays to poetry to computer code and even to movie scripts. However, there is no way to know today exactly how these technologies will change the ways that we teach, work, and learn. Thus, people tend to imagine different possible futures, and these imagined futures can shape their thinking about generative AI. This project studies the futures that college educators imagine around generative AI by examining discussions of classroom policies. For both introductory writing courses and introductory computer programming courses, the project team will analyze discussions among educators about how and why to form policies around using or prohibiting generative AI tools. Analyzing these discussions can help reveal the futures being imagined around generative AI and how those imagined futures are influencing our actions in the present. This project will also share results of the researchers' analysis with instructors who participate in the research, helping them to build a better sense of the space of possible policies they might use in their own classrooms.<br/><br/>The project includes two main lines of research activity. First, discussions about educational policies around generative AI will be collected from a range of online sources, including opinion pieces (e.g., in the Chronicle of Higher Education), social media discussions (e.g., in academic Reddit groups), and others. The researchers will analyze these discussion data using computational topic modeling to identify textual patterns indicative of latent suppositions and beliefs about possible sociotechnical futures. Second, researchers will conduct a series of qualitative interviews with instructors of two types of introductory college courses: courses on writing and composition, and courses on computer programming. These interviews will ask instructors directly about the futures that instructors imagine around generative AI, as well as how those imagined futures relate to their own course policies. The interviews will also include a reflexive component, where preliminary results from the above computational analysis are shared with participants. Doing so both serves as a member check on the results, i.e., comparing the research team's interpretations to those of the instructors themselves, and offers instructors an opportunity to reflect upon and contrast their own policies and imagined futures with those of other instructors. The results of this project will help lay a foundation for future research examining beliefs and policies about generative AI in a variety of application domains.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/28/2024
|
07/28/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2438704
|
[{'FirstName': 'Eric', 'LastName': 'Baumer', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eric P Baumer', 'EmailAddress': 'ericpsb@lehigh.edu', 'NSF_ID': '000581546', 'StartDate': '07/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Dominic', 'LastName': 'DiFranzo', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dominic DiFranzo', 'EmailAddress': 'djd219@lehigh.edu', 'NSF_ID': '000811406', 'StartDate': '07/28/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Lehigh University', 'CityName': 'BETHLEHEM', 'ZipCode': '180153008', 'PhoneNumber': '6107583021', 'StreetAddress': '526 BRODHEAD AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'PA07', 'ORG_UEI_NUM': 'E13MDBKHLDB5', 'ORG_LGL_BUS_NAME': 'LEHIGH UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Lehigh University', 'CityName': 'BETHLEHEM', 'StateCode': 'PA', 'ZipCode': '180153008', 'StreetAddress': '526 BRODHEAD AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'PA07'}
|
{'Code': '736700', 'Text': 'HCC-Human-Centered Computing'}
|
2024~131176
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438704.xml'}
|
Conference: Data-driven modeling and prediction of rare and extreme events
|
NSF
|
09/01/2024
|
08/31/2025
| 99,978 | 99,978 |
{'Value': 'Standard Grant'}
|
{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
|
{'SignBlockName': 'Alfred Hero', 'PO_EMAI': 'ahero@nsf.gov', 'PO_PHON': '7032920000'}
|
This workshop will convene experts in rare and extreme event detection and characterization representing a broad range of application domains and disciplines, including statistics, machine learning, applied mathematics, operations research, space weather, materials science, and climate modeling. Unanticipated rare and extreme events can be catastrophic in the domains of damaging high energy solar flares, sudden fuselage failure, and extreme terrestrial storms, causing significant loss of life and livelihood. Progress in modeling and predicting of such high risk events will require novel multidisciplinary approaches and this is what this conference seeks to uncover. It also seeks to catalyze new collaborations across these methodological and applicational domains. <br/><br/>The goal is of convening experts with complementary backgrounds is to identify key challenges and opportunities, with an emphasis on methodologies that may be leveraged across domains. The focus on data-driven methods encompasses recent efforts in machine learning, including physics-informed machine learning and generative models, and how such tools may advance rare and extreme event forecasting. The agenda will also include physics-driven approaches, including simulations, both as a source of fundamental insights into the modeling of rare events and as a mechanism for generating data to complement real-world data used to train data-driven models. This two-day workshop will be held at the University of Chicago on November 20-21, 2024. It will feature lectures from experts across the spectrum of disciplines listed above, panel discussions, poster sessions, and lightning talks.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/08/2024
|
08/08/2024
|
None
|
Grant
|
47.041, 47.049, 47.050, 47.070
|
1
|
4900
|
4900
|
2438847
|
{'FirstName': 'Rebecca', 'LastName': 'Willett', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rebecca M Willett', 'EmailAddress': 'willett@g.uchicago.edu', 'NSF_ID': '000312123', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Chicago', 'CityName': 'CHICAGO', 'ZipCode': '606375418', 'PhoneNumber': '7737028669', 'StreetAddress': '5801 S ELLIS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'IL01', 'ORG_UEI_NUM': 'ZUE9HKT2CLC9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CHICAGO', 'ORG_PRNT_UEI_NUM': 'ZUE9HKT2CLC9'}
|
{'Name': 'University of Chicago', 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606375418', 'StreetAddress': '5801 S ELLIS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'IL01'}
|
[{'Code': '126900', 'Text': 'STATISTICS'}, {'Code': '152300', 'Text': 'SOLAR-TERRESTRIAL'}, {'Code': '760700', 'Text': 'EPCN-Energy-Power-Ctrl-Netwrks'}, {'Code': '779700', 'Text': 'Comm & Information Foundations'}]
|
2024~99978
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438847.xml'}
|
Planning: DCL EPSCOR: SaTC Frontier: Toward Mitigating Supply Chain Risks in Autonomous Automotive Systems
|
NSF
|
10/01/2024
|
09/30/2025
| 100,000 | 100,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Ralph Wachter', 'PO_EMAI': 'rwachter@nsf.gov', 'PO_PHON': '7032928950'}
|
The security of supply chains is critical to ensuring the safety of systems and infrastructure that society depends on. The autonomous vehicle industry is an important and complex example of a system that (a) has large implications for safety and (b) relies on a wide variety of hardware and software elements in both the cars themselves and the roads they drive on. This makes connected and autonomous vehicles (CAVs) an excellent testbed for studying supply chain security questions. This project will support the planning of a large-scale SaTC Frontier proposal to advance science, education, and workforce development around supply chain security for CAVs. The eventual proposal will include identifying key security and privacy risks around CAV supply chains, developing methods to address them, and creating new courses and educational materials to better train a workforce ready to deal with critical supply chain security issues in CAVs and beyond.<br/><br/>The project's goal is to develop a fully realized proposal in terms of the scientific questions, team and partnerships, and social impacts to be addressed. To do this the research team plans a number of activities with industry and academic partners. A seminar series and visits between the host institution and potential partners will develop both a better understanding of the problems and the foundation for advisory and research partnerships in the eventual full proposal. A workshop focused on CAV supply chain security associated with a large international conference will bring a wider community together. There are also plans to work with nearby institutions to broaden and widen the team's research expertise, as well as gaining expertise in how to structure and manage large research teams from the leaders of existing SaTC Frontier awards. Through these efforts the team will develop the knowledge, resources, and people required to create a high-quality, large-scale proposal.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/22/2024
|
08/22/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2438898
|
[{'FirstName': 'Xu', 'LastName': 'Yuan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xu Yuan', 'EmailAddress': 'xyuan@udel.edu', 'NSF_ID': '000760834', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Xing', 'LastName': 'Gao', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xing Gao', 'EmailAddress': 'xgao@udel.edu', 'NSF_ID': '000784502', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Satwik', 'LastName': 'Patnaik', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Satwik Patnaik', 'EmailAddress': 'satwik@udel.edu', 'NSF_ID': '000867029', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Delaware', 'CityName': 'NEWARK', 'ZipCode': '197160099', 'PhoneNumber': '3028312136', 'StreetAddress': '220 HULLIHEN HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Delaware', 'StateCode': 'DE', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DE00', 'ORG_UEI_NUM': 'T72NHKM259N3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF DELAWARE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Delaware', 'CityName': 'NEWARK', 'StateCode': 'DE', 'ZipCode': '197160099', 'StreetAddress': '220 HULLIHEN HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Delaware', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DE00'}
|
{'Code': '164000', 'Text': 'Information Technology Researc'}
|
2024~100000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438898.xml'}
|
Conference: CI PAOS: FAIROS Research Coordination Network PI Workshop
|
NSF
|
09/01/2024
|
08/31/2025
| 65,554 | 65,554 |
{'Value': 'Standard Grant'}
|
{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}
|
{'SignBlockName': 'Plato Smith', 'PO_EMAI': 'plsmith@nsf.gov', 'PO_PHON': '7032924278'}
|
NSF FAIROS Research Coordination Networks (RCNs) work to build and enhance coordination of researchers and other stakeholders advancing Findable, Accessible, Interoperable, and Reusable (FAIR) data principles and Open Science (OS) practices. The initial cohort of 10 awards span a wide range of disciplines and have advanced FAIR-OS efforts as well as convened RCN-specific events. To broaden their impact and focus future directions, it is an appropriate time to take stock of RCN efforts and work together to both contextualize successes and clarify gaps as needed to plan sustained efforts in FAIR and Open Science across the US Science research landscape.<br/><br/>This PI Meeting will support a community-driven and community-focused effort to help define the role that federal agencies can play in accelerating the pace of FAIROS. The workshop will bring together the research teams in their varied stages of maturity to encourage and support those in their early years while providing new ideas for more mature efforts facing persistent gaps.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/09/2024
|
08/09/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2438914
|
{'FirstName': 'David', 'LastName': 'Elbert', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David Elbert', 'EmailAddress': 'elbert@jhu.edu', 'NSF_ID': '000786902', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Johns Hopkins University', 'CityName': 'BALTIMORE', 'ZipCode': '212182608', 'PhoneNumber': '4439971898', 'StreetAddress': '3400 N CHARLES ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MD07', 'ORG_UEI_NUM': 'FTMTDMBR29C7', 'ORG_LGL_BUS_NAME': 'THE JOHNS HOPKINS UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Johns Hopkins University', 'CityName': 'BALTIMORE', 'StateCode': 'MD', 'ZipCode': '212182608', 'StreetAddress': '3400 N CHARLES ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MD07'}
|
{'Code': '741400', 'Text': 'NSF Public Access Initiative'}
|
2024~65554
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438914.xml'}
|
Planning: DCL EPSCOR: CISE Large: Investigations in Foundational Models for Recommendation with Applications to Complex Domains
|
NSF
|
10/01/2024
|
09/30/2025
| 100,000 | 100,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Ralph Wachter', 'PO_EMAI': 'rwachter@nsf.gov', 'PO_PHON': '7032928950'}
|
Recommender systems use machine learning to learn about people's preferences from their feedback. These systems then suggest a small, relevant subset of options from a large pool, tailored to each user's needs. Recommender systems help users find items they might not have discovered on their own, changing how they consume information and reducing the time spent searching. Despite significant progress over the years, recommender systems still face challenges with fairness, including issues of bias and transparency. On the other hand, generative AI, in particular Large Language Models (LLMs), are creating significant new opportunities as well as potential challenges for information access. There is a crucial need to find better, sustainable ways to continue innovating with LLMs while ensuring more equitable benefits. This requires working on fundamental issues of fairness, robustness and trustworthiness and, more generally, a responsible use of AI with respect to communities and the environment. For all these reasons, Large Language Models, when used to power recommender systems, and especially when used to expand human exploration, can have a significant impact on society, in terms of education, economic impact, and equity. <br/><br/>This planning award will support the team to build on promising preliminary work and ideas to mount a competitive large-scale impactful CISE core project and proposal, driven by ambitious research, education, and broadening participation goals. The team will investigate novel algorithms for incorporating foundational models, in particular large language models in recommendation systems while anchoring all methods in expanded fairness criteria. The research will address core issues of fairness, robustness, and trustworthiness, and, more generally, a responsible use of AI with respect to communities and the environment in which they live. In particular the research will address multifaceted fairness desiderata that transcend traditional model predictive performance and fairness metrics throughout the various stages of the Large Language Model-based recommender system pipeline. During the planning phase, the team will engage with diverse stakeholders to assess the needs and shape their ideas. In addition to having a number of novel ideas with promising preliminary work, the team has identified several potential application domains with different use cases. These ideas and use cases need to be narrowed down and organized within a competitive and sound plan, along with the formation of an interdisciplinary team from among a potentially large number of stakeholders throughout the team’s institutions and communities. The planning grant will allow the team to incorporate several of their preliminary research ideas int use-inspired research and further mount a comprehensive plan with direct impact on education and broadening participation.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/26/2024
|
08/26/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2438935
|
[{'FirstName': 'Olfa', 'LastName': 'Nasraoui', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Olfa Nasraoui', 'EmailAddress': 'olfa.nasraoui@louisville.edu', 'NSF_ID': '000367596', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Chirag', 'LastName': 'Shah', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Chirag Shah', 'EmailAddress': 'chirags@uw.edu', 'NSF_ID': '000573357', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Louisville Research Foundation Inc', 'CityName': 'LOUISVILLE', 'ZipCode': '402081838', 'PhoneNumber': '5028523788', 'StreetAddress': '2301 S 3RD ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Kentucky', 'StateCode': 'KY', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'KY03', 'ORG_UEI_NUM': 'E1KJM4T54MK6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF LOUISVILLE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Louisville Research Foundation', 'CityName': 'Louisville', 'StateCode': 'KY', 'ZipCode': '402021959', 'StreetAddress': '300 East Market Street', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Kentucky', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'KY03'}
|
{'Code': '164000', 'Text': 'Information Technology Researc'}
|
2024~100000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438935.xml'}
|
Planning: DCL-EPSCOR: SaTC Frontier: Exploring the Synergy Between Generative AI and Cybersecurity
|
NSF
|
10/01/2024
|
09/30/2025
| 100,000 | 100,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Ralph Wachter', 'PO_EMAI': 'rwachter@nsf.gov', 'PO_PHON': '7032928950'}
|
Generative AI systems, which can produce text, images, and other content, are increasingly commonly used. However, from a security and privacy perspective, these systems pose a number of risks. Generative AI systems can violate the property and privacy rights of the people whose data are used to build them. They can also be used to generate content that might trick people into making mistakes that affect their security, privacy, and beliefs. On the other hand, generative AI systems might be used to support security and privacy goals. They may be able to create synthetic data that helps detect and predict new attacks more rapidly, which in turn could be used to make safer software, policies, and security operations practices. This project's goal is to support the planning of a large-scale proposal to study the risks and benefits that Generative AI-based systems may pose to security and privacy, developing methods to increase their safety and usefulness for society.<br/><br/>The project's goal is to develop a fully realized proposal in terms of the scientific questions, team and partnerships, and social impacts to be addressed. To do this the research team will start with project ideation and identification of key stakeholders in both the scientific and social impact realms. These efforts will be based on established methods for identifying and learning from those affected by projects, including interviews, workshops, and community-building meetups. The research team will also identify an external advisory board and evaluation team to guide the project as it goes forward. Through these efforts, the team will develop the knowledge, resources, and people required to create a high-quality, large-scale proposal.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/28/2024
|
08/28/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2438950
|
[{'FirstName': 'Warren', 'LastName': 'Alexander', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Warren P Alexander', 'EmailAddress': 'perry.alexander@ku.edu', 'NSF_ID': '000398340', 'StartDate': '08/28/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Michael', 'LastName': 'Branicky', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael S Branicky', 'EmailAddress': 'msb@ku.edu', 'NSF_ID': '000269486', 'StartDate': '08/28/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Bo', 'LastName': 'Luo', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Bo Luo', 'EmailAddress': 'bluo@ittc.ku.edu', 'NSF_ID': '000521104', 'StartDate': '08/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Fengjun', 'LastName': 'Li', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Fengjun Li', 'EmailAddress': 'fli@ku.edu', 'NSF_ID': '000613726', 'StartDate': '08/28/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jennifer', 'LastName': 'Lohoefener', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jennifer Lohoefener', 'EmailAddress': 'jlohoefener@ku.edu', 'NSF_ID': '000827100', 'StartDate': '08/28/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Kansas Center for Research Inc', 'CityName': 'LAWRENCE', 'ZipCode': '660457563', 'PhoneNumber': '7858643441', 'StreetAddress': '2385 IRVING HILL RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Kansas', 'StateCode': 'KS', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'KS01', 'ORG_UEI_NUM': 'SSUJB3GSH8A5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF KANSAS CENTER FOR RESEARCH INC', 'ORG_PRNT_UEI_NUM': 'SSUJB3GSH8A5'}
|
{'Name': 'University of Kansas Center for Research Inc', 'CityName': 'LAWRENCE', 'StateCode': 'KS', 'ZipCode': '660457563', 'StreetAddress': '2385 IRVING HILL RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Kansas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'KS01'}
|
{'Code': '164000', 'Text': 'Information Technology Researc'}
|
2024~100000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438950.xml'}
|
Planning: DCL EPSCOR: CISE Large: Sensing, Planning, and Acting in a Multi-Human, Multi-Aerial Vehicle Job Site
|
NSF
|
10/01/2024
|
09/30/2026
| 200,000 | 200,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Ralph Wachter', 'PO_EMAI': 'rwachter@nsf.gov', 'PO_PHON': '7032928950'}
|
Consider a world in which any user could safely and reliably employ uncrewed aerial systems (or drones) in their work to help with data collection, interaction with the natural or built environment, and even social interactions at work sites rather than as specialty tools with specialist users. While these systems have become pervasive individually, they lack the fundamental understanding of how to work in teams with each other and humans to accomplish larger goals on job sites. This planning project explores ideas to address the intertwined challenges of communicating amongst users and vehicles in a clear, resilient way to allow safe, reliable interactions in diverse use cases, to distill foundational requirements and constructs for multi-user, multi-drone interactions. This future technology would require work across many disciplines to understand what interfaces are necessary, recognize features of safe interactions between users and across environments, learn how people adopt this technology and how it should adapt to users, codify all of these interactions in robust ways, and develop tests for both the safety and integration of different components. <br/><br/>The goal of this planning project is to develop the initial conceptualization, planning and collaboration activities that aim to formulate new and sound plans for large-scale projects in these emerging research areas. It brings together teams of researchers in supporting science, technology and applications to develop the concepts and plans to transform the design of human-drone interactions, enabling safer ubiquity on job sites and overcoming the current limitations of siloed deployment and software. It looks holistically at the human-drone team, understanding components of interaction that are generalizable across contexts, and developing systems which can be used anywhere to enable safer, more efficient teaming. This research planning project focuses on radically improving communications, developing methodologies for close interactions in independent multi-human-robot teams, and tools to support interactions with diverse users in applications such as construction and search-and-rescue.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/22/2024
|
08/22/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2438976
|
[{'FirstName': 'Brittany', 'LastName': 'Duncan', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Brittany A Duncan', 'EmailAddress': 'bduncan@unl.edu', 'NSF_ID': '000703906', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Joshua', 'LastName': 'Peschel', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Joshua M Peschel', 'EmailAddress': 'peschel@iastate.edu', 'NSF_ID': '000738382', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Nebraska-Lincoln', 'CityName': 'LINCOLN', 'ZipCode': '685032427', 'PhoneNumber': '4024723171', 'StreetAddress': '2200 VINE ST # 830861', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Nebraska', 'StateCode': 'NE', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NE01', 'ORG_UEI_NUM': 'HTQ6K6NJFHA6', 'ORG_LGL_BUS_NAME': 'BOARD OF REGENTS OF THE UNIVERSITY OF NEBRASKA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Nebraska-Lincoln', 'CityName': 'LINCOLN', 'StateCode': 'NE', 'ZipCode': '685032427', 'StreetAddress': '2200 VINE ST # 830861', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Nebraska', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NE01'}
|
{'Code': '164000', 'Text': 'Information Technology Researc'}
|
2024~200000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438976.xml'}
|
NSF-SNSF: Continuous evolution of artificial catalysts into life-sustaining enzymes
|
NSF
|
08/15/2024
|
07/31/2028
| 650,546 | 650,546 |
{'Value': 'Standard Grant'}
|
{'Code': '08070000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'MCB', 'LongName': 'Div Of Molecular and Cellular Bioscience'}}
|
{'SignBlockName': 'Anthony Garza', 'PO_EMAI': 'aggarza@nsf.gov', 'PO_PHON': '7032922489'}
|
This project will use a state-of-the-art rapid gene evolution system to change relatively simple enzymes into enzymes with advanced capabilities that extend beyond those found in nature. In doing this, this project will help us understand how enzymes upgrade their performance over long periods of time, provide blueprints for enzyme design, and contribute to synthetic biology, and potentially biotechnology, medicine, agriculture and the bioeconomy.<br/><br/>Like most processes involving long natural evolutionary timescales, the emergence of complex enzymes from what were presumably simple biocatalysts early in life's history has not been directly observed. The investigators have developed a powerful synthetic evolution system called orthogonal DNA replication (OrthoRep) that drives the in vivo continuous evolution of chosen genes at mutation rates one million-fold higher than those of the host genome. OrthoRep compresses gene evolution processes that naturally take thousands to millions of years into weeks-long laboratory experiments involving just the passaging of cells. The investigators propose using OrthoRep to prospectively evolve “simple” primitive catalysts into “advanced” biological enzymes. The simple catalysts from which we will start evolution are artificial metalloenzymes (ArMs), chosen because they mimic the putative organization of primordial enzymes in early life where catalytic performance is predominantly localized to a cofactor attached to a protein scaffold. They will evolve ArMs into advanced enzymes, guided by the hypothesis that the evolutionary emergence and optimization of interconnected amino acid networks coupling the active site to sectors across an entire protein is responsible for the exceptional performance of modern enzymes.<br/><br/>This collaborative US/Switzerland project is supported by the US National Science Foundation (NSF) and the Swiss National Science Foundation (S-NSF), where NSF funds the US investigator and S-NSF funds the partners in Switzerland. Within NSF, the project is co-funded by Office of International Science and Engineering, and the Systems and Synthetic Biology Program in the Division of Molecular and Cellular Biosciences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/07/2024
|
08/07/2024
|
None
|
Grant
|
47.074, 47.079
|
1
|
4900
|
4900
|
2438980
|
{'FirstName': 'Chang', 'LastName': 'Liu', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Chang C Liu', 'EmailAddress': 'ccl@uci.edu', 'NSF_ID': '000695337', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-Irvine', 'CityName': 'IRVINE', 'ZipCode': '926970001', 'PhoneNumber': '9498247295', 'StreetAddress': '160 ALDRICH HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '47', 'CONGRESS_DISTRICT_ORG': 'CA47', 'ORG_UEI_NUM': 'MJC5FCYQTPE6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA IRVINE', 'ORG_PRNT_UEI_NUM': 'MJC5FCYQTPE6'}
|
{'Name': 'University of California-Irvine', 'CityName': 'IRVINE', 'StateCode': 'CA', 'ZipCode': '926972700', 'StreetAddress': '4064 Samueli Interdisciplinary Science and Engineering', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '47', 'CONGRESS_DISTRICT_PERF': 'CA47'}
|
[{'Code': '054Y00', 'Text': 'GVF - Global Venture Fund'}, {'Code': '801100', 'Text': 'Systems and Synthetic Biology'}]
|
2024~650546
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438980.xml'}
|
Collaborative Research: MODULUS: Copy Number Alterations and Xenobiotic adaptation
|
NSF
|
11/01/2023
|
04/30/2025
| 416,605 | 308,431 |
{'Value': 'Standard Grant'}
|
{'Code': '08070000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'MCB', 'LongName': 'Div Of Molecular and Cellular Bioscience'}}
|
{'SignBlockName': 'David Rockcliffe', 'PO_EMAI': 'drockcli@nsf.gov', 'PO_PHON': '7032927123'}
|
Understanding evolution is fundamental to understanding life on earth. Evolution also creates some of the greatest challenges to human health. Viruses, bacteria, fungi, and cancer cells all evolve resistance to xenobiotics. These xenobiotics are molecules that are not found naturally but that influence evolution in the natural world. This project aims to create new theory and experiments to understand xenobiotic evolution. The results of this project would have applications across many different fields such as bacteria resistant to antibiotics, malaria parasites resistant to antimalarial drugs, tumor cells resistant to cancer drugs, plants resistant to herbicides, and insects resistant to insecticides. The award provides support to train STEM graduate students that will eventually become part of the workforce. The project also provides research opportunities for undergraduates and develops new educational games that teach K-12 students about science, using xenobiotic evolution as an example.<br/><br/>The main goal of this project is to discover novel aspects of xenobiotic adaptation that result from the interactions between mutations and gene amplifications. The project examines the complex, nonlinear evolutionary pathways that lead to xenobiotic adaptation in the context of antibiotic resistance evolution induced by Rifampin in E. coli. Mathematically, the project would model resistance evolution as a function of plasmid copy number with the use of a stochastic process that accounts for tunneling rates and spatial structures of the community of evolving cells. The project makes use of an incoherent feed forward loop that gives synthetic control for providing variation in plasmid copy numbers in cells while keeping biochemical levels constant. Synthetic biology experiments are designed with a view to parametrizing the models under development and exploring the effects of specific parameters that have been indicated as important by the model.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/26/2024
|
07/26/2024
|
None
|
Grant
|
47.049, 47.074
|
1
|
4900
|
4900
|
2438986
|
{'FirstName': 'Natalia', 'LastName': 'Komarova', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Natalia Komarova', 'EmailAddress': 'nkomarova@ucsd.edu', 'NSF_ID': '000485742', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'ZipCode': '920930021', 'PhoneNumber': '8585344896', 'StreetAddress': '9500 GILMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_ORG': 'CA50', 'ORG_UEI_NUM': 'UYTTZT6G9DT1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, SAN DIEGO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'StateCode': 'CA', 'ZipCode': '920930021', 'StreetAddress': '9500 GILMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_PERF': 'CA50'}
|
[{'Code': '745400', 'Text': 'MSPA-INTERDISCIPLINARY'}, {'Code': '801100', 'Text': 'Systems and Synthetic Biology'}]
|
2022~308430
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2438986.xml'}
|
Planning: DCL EPSCOR: SaTC Frontier: Ensuring Security and Privacy in AI-Enabled Cyber-Physical Systems
|
NSF
|
10/01/2024
|
09/30/2026
| 199,973 | 199,973 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Ralph Wachter', 'PO_EMAI': 'rwachter@nsf.gov', 'PO_PHON': '7032928950'}
|
Artificial intelligence (AI) is increasingly used in cyber-physical systems (CPSs) that directly sense and interact with the environment to help them react to large, real-time data that comes in a variety of formats. However, the security and safety of AI models, and the privacy of the data used to build them, can be attacked. There is some research on AI model safety in other domains, but in CPSs the nature and scale of attacks on AI models may change because of their connection to the wider environment. This project will support planning a large-scale proposal to increase the security and privacy of AI-enabled CPSs. This will involve developing foundational knowledge and systematic tools to understand and defend against the unique risks of AI-enabled CPSs. It will also involve creating an engineering and education community capable of using that knowledge and those tools to build safer, more secure systems that help society better-interact with the world.<br/><br/>The planning project is led by an interdisciplinary team with expertise in AI, machine learning, and CPS security. To better understand the challenges across a variety of CPS contexts, and provide resources for both expertise and deployment, the research team will collaborate with experts from a number of CPS domains, including space science, healthcare, transportation, and water resource management. The team will also work with stakeholders in education, business, the wider academic community, and government to inform questions and activities related to the project's education and workforce development goals. Planning activities include a series of biweekly seminars, quarterly newsletters, and symposia; these will support frequent communication and coordination around developing both the proposal itself and team required to execute it.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/28/2024
|
08/28/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2439013
|
[{'FirstName': 'Jodi-Ann', 'LastName': 'Ito', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jodi-Ann Ito', 'EmailAddress': 'jodi@hawaii.edu', 'NSF_ID': '000473874', 'StartDate': '08/28/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Hongyi', 'LastName': 'Wu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hongyi Wu', 'EmailAddress': 'mhwu@arizona.edu', 'NSF_ID': '000184931', 'StartDate': '08/28/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Yingfei', 'LastName': 'Dong', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yingfei Dong', 'EmailAddress': 'yingfei@hawaii.edu', 'NSF_ID': '000039421', 'StartDate': '08/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Liuwan', 'LastName': 'Zhu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Liuwan Zhu', 'EmailAddress': 'liuwan@hawaii.edu', 'NSF_ID': '000988739', 'StartDate': '08/28/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'University of Hawaii', 'CityName': 'HONOLULU', 'ZipCode': '968222247', 'PhoneNumber': '8089567800', 'StreetAddress': '2425 CAMPUS RD SINCLAIR RM 1', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Hawaii', 'StateCode': 'HI', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'HI01', 'ORG_UEI_NUM': 'NSCKLFSSABF2', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF HAWAII', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Hawaii', 'CityName': 'HONOLULU', 'StateCode': 'HI', 'ZipCode': '968222247', 'StreetAddress': '2425 CAMPUS RD SINCLAIR RM 1', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Hawaii', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'HI01'}
|
{'Code': '164000', 'Text': 'Information Technology Researc'}
|
2024~199973
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439013.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 1,237,277 | 1,237,277 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/23/2024
|
08/23/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439018
|
{'FirstName': 'Sara', 'LastName': 'Wadia-Fascetti', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sara Wadia-Fascetti', 'EmailAddress': 'swf@neu.edu', 'NSF_ID': '000441316', 'StartDate': '08/23/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'ZipCode': '021155005', 'PhoneNumber': '6173733004', 'StreetAddress': '360 HUNTINGTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'HLTMVS2JZBS6', 'ORG_LGL_BUS_NAME': 'NORTHEASTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Northeastern University', 'CityName': 'Boston', 'StateCode': 'MA', 'ZipCode': '021155005', 'StreetAddress': '360 HUNTINGTON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~1237277
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439018.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 159,000 | 159,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439020
|
{'FirstName': 'Rossitza', 'LastName': 'Wooster', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rossitza B Wooster', 'EmailAddress': 'wooster@pdx.edu', 'NSF_ID': '000523726', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Portland State University', 'CityName': 'PORTLAND', 'ZipCode': '972015508', 'PhoneNumber': '5037259900', 'StreetAddress': '1600 SW 4TH AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oregon', 'StateCode': 'OR', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'OR01', 'ORG_UEI_NUM': 'H4CAHK2RD945', 'ORG_LGL_BUS_NAME': 'PORTLAND STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'WWUJS84WJ647'}
|
{'Name': 'Portland State University', 'CityName': 'Portland', 'StateCode': 'OR', 'ZipCode': '972015508', 'StreetAddress': '1600 SW 4TH AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oregon', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'OR01'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~159000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439020.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 225,933 | 225,933 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439023
|
{'FirstName': 'Stephanie', 'LastName': 'Lezotte', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stephanie M Lezotte', 'EmailAddress': 'lezotte@rowan.edu', 'NSF_ID': '000552390', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Rowan University', 'CityName': 'GLASSBORO', 'ZipCode': '080281700', 'PhoneNumber': '8562564057', 'StreetAddress': '201 MULLICA HILL RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NJ01', 'ORG_UEI_NUM': 'DMDEQP66JL85', 'ORG_LGL_BUS_NAME': 'ROWAN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Rowan University', 'CityName': 'GLASSBORO', 'StateCode': 'NJ', 'ZipCode': '080281700', 'StreetAddress': '201 MULLICA HILL RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NJ01'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~225933
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439023.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 3,107,253 | 3,107,253 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439024
|
{'FirstName': 'Jean-Pierre', 'LastName': 'Delplanque', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jean-Pierre R Delplanque', 'EmailAddress': 'delplanque@ucdavis.edu', 'NSF_ID': '000486289', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-Davis', 'CityName': 'DAVIS', 'ZipCode': '956186153', 'PhoneNumber': '5307547700', 'StreetAddress': '1850 RESEARCH PARK DR STE 300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'CA04', 'ORG_UEI_NUM': 'TX2DAGQPENZ5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, DAVIS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Davis', 'CityName': 'DAVIS', 'StateCode': 'CA', 'ZipCode': '956186153', 'StreetAddress': '1850 RESEARCH PARK DR STE 300', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'CA04'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~3107253
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439024.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 212,000 | 212,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439025
|
{'FirstName': 'Rose Marie', 'LastName': 'Ward', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rose Marie Ward', 'EmailAddress': 'wardrm@ucmail.uc.edu', 'NSF_ID': '000583340', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Cincinnati Main Campus', 'CityName': 'CINCINNATI', 'ZipCode': '452202872', 'PhoneNumber': '5135564358', 'StreetAddress': '2600 CLIFTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'OH01', 'ORG_UEI_NUM': 'DZ4YCZ3QSPR5', 'ORG_LGL_BUS_NAME': 'CINCINNATI UNIV OF', 'ORG_PRNT_UEI_NUM': 'DZ4YCZ3QSPR5'}
|
{'Name': 'University of Cincinnati Main Campus', 'CityName': 'CINCINNATI', 'StateCode': 'OH', 'ZipCode': '452202872', 'StreetAddress': '2600 CLIFTON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'OH01'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~212000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439025.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/01/2024
|
07/31/2029
| 478,514 | 478,514 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/23/2024
|
07/23/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439026
|
{'FirstName': 'Jennifer', 'LastName': 'RIcher', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jennifer RIcher', 'EmailAddress': 'jennifer.richer@cuanschutz.edu', 'NSF_ID': '000711512', 'StartDate': '07/23/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Colorado at Denver', 'CityName': 'AURORA', 'ZipCode': '800452571', 'PhoneNumber': '3037240090', 'StreetAddress': '13001 E 17TH PL STE F428', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'CO06', 'ORG_UEI_NUM': 'MW8JHK6ZYEX8', 'ORG_LGL_BUS_NAME': 'THE REGENTS OF THE UNIVERSITY OF COLORADO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Colorado at Denver', 'CityName': 'AURORA', 'StateCode': 'CO', 'ZipCode': '800452571', 'StreetAddress': '13001 E 17TH PL STE F428', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'CO06'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~478514
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439026.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 53,000 | 53,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439028
|
{'FirstName': 'John', 'LastName': 'Lukesh', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': 'III', 'PI_FULL_NAME': 'John C Lukesh', 'EmailAddress': 'lukeshjc@wfu.edu', 'NSF_ID': '000804694', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Wake Forest University', 'CityName': 'WINSTON SALEM', 'ZipCode': '271096000', 'PhoneNumber': '3367585888', 'StreetAddress': '1834 WAKE FOREST RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'NC05', 'ORG_UEI_NUM': 'MBU6HCLNZ431', 'ORG_LGL_BUS_NAME': 'WAKE FOREST UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Wake Forest University', 'CityName': 'WINSTON SALEM', 'StateCode': 'NC', 'ZipCode': '271096000', 'StreetAddress': '1834 WAKE FOREST RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'NC05'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~53000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439028.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 318,000 | 318,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439031
|
{'FirstName': 'Terri', 'LastName': 'Camesano', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Terri A Camesano', 'EmailAddress': 'terric@wpi.edu', 'NSF_ID': '000147507', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Worcester Polytechnic Institute', 'CityName': 'WORCESTER', 'ZipCode': '016092247', 'PhoneNumber': '5088315000', 'StreetAddress': '100 INSTITUTE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'MA02', 'ORG_UEI_NUM': 'HJNQME41NBU4', 'ORG_LGL_BUS_NAME': 'WORCESTER POLYTECHNIC INSTITUTE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Worcester Polytechnic Institute', 'CityName': 'WORCESTER', 'StateCode': 'MA', 'ZipCode': '016092247', 'StreetAddress': '100 INSTITUTE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'MA02'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~318000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439031.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 505,800 | 505,800 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439032
|
{'FirstName': 'Richard', 'LastName': 'Souvenir', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Richard Souvenir', 'EmailAddress': 'souvenir@temple.edu', 'NSF_ID': '000730388', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Temple University', 'CityName': 'PHILADELPHIA', 'ZipCode': '191226104', 'PhoneNumber': '2157077547', 'StreetAddress': '1805 N BROAD ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'PA02', 'ORG_UEI_NUM': 'QD4MGHFDJKU1', 'ORG_LGL_BUS_NAME': 'TEMPLE UNIVERSITY-OF THE COMMONWEALTH SYSTEM OF HIGHER EDUCATION', 'ORG_PRNT_UEI_NUM': 'QD4MGHFDJKU1'}
|
{'Name': 'Temple University', 'CityName': 'PHILADELPHIA', 'StateCode': 'PA', 'ZipCode': '191226104', 'StreetAddress': '1805 N BROAD ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'PA02'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~505800
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439032.xml'}
|
FW-HTF-P: Integrating Practitioner Knowledge and Technology for the Future of Water Treatment
|
NSF
|
12/15/2023
|
02/28/2025
| 150,000 | 36,171 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Alexandra Medina-Borja', 'PO_EMAI': 'amedinab@nsf.gov', 'PO_PHON': '7032927557'}
|
Municipal water treatment involves chemical and physical processes to “clean” the water based upon the intake water quality. While not typically harmful, presence of tastes and odors can lead to customer dissatisfaction and skepticism about the safety and reliability of the water. Loss of customer confidence can result in loss of revenue for the financially strained utilities and/or customers turning to less healthy or less safe alternatives. To date, water treatment plant (WTP) operators typically add activated carbon in incremental doses to remove the tastes and odors. When and how much carbon is added depends on weather, intake water quality, and other factors. Ongoing research suggests that operators have developed a “sense” for how to manage the seasonal taste and odor issues at his/her plant based on years of experience. Coupling the treatment challenges and current approach with a workforce approaching retirement, and a new generation that may lack the long-term experience of managing taste and odor issues provides the motivation for this research. The research team will engage with current operators through a national-level survey, a workshop, and focus group meetings to “learn” how they make operational decisions in the treatment of taste and odors. This project is a first attempt to capture and understand the decision processes and outcomes of the experienced workforce for current and future operator decision support. <br/><br/>In this project, the research team will be facilitating collaboration across disciplines and working toward development of conceptual models of the decision-making process of operators. Ongoing research is finding that some water treatment procedures, including management of tastes and odors, depend primarily on intuition and experience rather than on definite science. This operational approach will likely pose challenges in coping with more extreme/significant events that may be prompted by growing populations and associated land changes, climatic changes, etc. As the operator workforce ages out, the next generation lacks the experience and intuition/knowledge that comes with time to adapt and respond to these changes. The project team is collecting data from current WTP operators through both qualitative and quantitative methods to document and better understand the decision-making processes related to municipal water treatment. Models of these data will allow decisions to be replicated to support improved decision support for both current and future operators.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/24/2024
|
07/24/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2439081
|
{'FirstName': 'Janey', 'LastName': 'Camp', 'PI_MID_INIT': 'V', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Janey V Camp', 'EmailAddress': 'jvcamp@memphis.edu', 'NSF_ID': '000561136', 'StartDate': '07/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Memphis', 'CityName': 'MEMPHIS', 'ZipCode': '381520001', 'PhoneNumber': '9016783251', 'StreetAddress': '115 JOHN WILDER TOWER', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Tennessee', 'StateCode': 'TN', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'TN09', 'ORG_UEI_NUM': 'F2VSMAKDH8Z7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MEMPHIS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Memphis', 'CityName': 'MEMPHIS', 'StateCode': 'TN', 'ZipCode': '381520001', 'StreetAddress': '115 JOHN WILDER TOWER', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Tennessee', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'TN09'}
|
{'Code': '103Y00', 'Text': 'FW-HTF Futr Wrk Hum-Tech Frntr'}
|
2021~36171
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439081.xml'}
|
Investigating Community College to PhD: Developing Graduate Aspirations Among Upward Transfer Students in Computing and Technology
|
NSF
|
07/01/2024
|
06/30/2025
| 688,454 | 179,142 |
{'Value': 'Standard Grant'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Andrea Nixon', 'PO_EMAI': 'anixon@nsf.gov', 'PO_PHON': '7032922321'}
|
The study will investigate whether participation in early intervention positively predicts graduate school aspirations and enrollment among upward transfer community college computing students and whether this differs by gender, race/ethnicity, first generation college status, or socioeconomic status. The college study also will consider factors that shape their decision making. The intervention will be implemented across five campuses within the University of California system, tracking students from the time they transfer to one of the campuses through matriculation unto graduate programs in computing. By empirically examining the impact of different aspects of the intervention, the study will provide guidance for how to most efficiently promote graduate school aspirations and intentions among upward transfer students in computing and other STEM fields.<br/><br/>Guided by Social Cognitive Career Theory (SCCT), the study will investigate four research questions: (1) Does participation in the early intervention program positively predict graduate school aspirations and enrollment among upward transfer computing students? Does this differ by gender, race/ethnicity, first-generation college status, or socioeconomic status? (2) What other post-transfer experiences predict graduate aspirations and enrollment among upward transfers in computing? (3) How do upward transfer students experience and make meaning of the early intervention program? And (4) How do upward transfer students aspire to graduate school in computing? What factors shape their decision making? Investigators will employ multiple methods to examine the longitudinal impact of the proposed intervention and a Staged Innovation Design to analyze the data. The project could inform the design of pathways from community college to doctoral programs in computing, thereby, diversifying the computing faculty. <br/><br/>The award is funded by the EHR Core Research (ECR) program, STEM professional workforce development theme. ECR supports fundamental research that addresses STEM learning and learning environments, broadening participation in STEM, and STEM workforce development.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/07/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439166
|
{'FirstName': 'Jennifer', 'LastName': 'Blaney', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jennifer M Blaney', 'EmailAddress': 'jennifer.blaney@uga.edu', 'NSF_ID': '000808681', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Georgia Research Foundation Inc', 'CityName': 'ATHENS', 'ZipCode': '306021589', 'PhoneNumber': '7065425939', 'StreetAddress': '310 E CAMPUS RD RM 409', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'GA10', 'ORG_UEI_NUM': 'NMJHD63STRC5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF GEORGIA RESEARCH FOUNDATION, INC.', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Georgia', 'CityName': 'ATHENS', 'StateCode': 'GA', 'ZipCode': '306021589', 'StreetAddress': '310 E CAMPUS RD RM 409', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'GA10'}
|
[{'Code': '199700', 'Text': 'NSF Research Traineeship (NRT)'}, {'Code': '798000', 'Text': 'ECR-EDU Core Research'}]
|
['2020~69022', '2024~110120']
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439166.xml'}
|
CRII: AF: Efficiently Computing and Updating Topological Descriptors for Data Analysis
|
NSF
|
07/15/2024
|
03/31/2026
| 160,230 | 156,058 |
{'Value': 'Standard Grant'}
|
{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
|
{'SignBlockName': 'Peter Brass', 'PO_EMAI': 'pbrass@nsf.gov', 'PO_PHON': '7032922182'}
|
Harnessing the power of data has been a driving force for computing, especially in recent years when breakthroughs in data science enable computers to perform tasks never seen before. However, as the data becomes more and more complex, there is also a growing need for more advanced techniques to uncover the hidden structures of data. Using tools in a branch of mathematics, namely topology, Topological Data Analysis (TDA) aims at revealing the 'shape' of data that are otherwise not easily captured by traditional methods. However, the computational complexity of some important data descriptors proposed in TDA is not very well-understood, which is a major obstacle to their wider applications. This project aims at devising efficient algorithms for computing these important data descriptors. Efficient software for the computation will be developed, which is a necessary step for promoting applications. Efforts of the project will help train undergraduate or graduate students by enabling them to cultivate mathematical and algorithmic thinking through the software development process.<br/><br/>Two foci of this project are the following descriptors revolving around persistent homology (a cornerstone of TDA) and its extension zigzag persistence: (i) representatives for topological persistence; (ii) vines and vineyard from updating the standard and zigzag persistence. Novel data structures dedicated to the computation will be devised. From the study, a deeper connection between the mathematical objects and their algorithmic interpretation can be established, which can have further implications on the computational front of TDA.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/22/2024
|
08/22/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2439255
|
{'FirstName': 'Tao', 'LastName': 'Hou', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tao Hou', 'EmailAddress': 'taohou@uoregon.edu', 'NSF_ID': '000940286', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Oregon Eugene', 'CityName': 'EUGENE', 'ZipCode': '974031905', 'PhoneNumber': '5413465131', 'StreetAddress': '1776 E 13TH AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oregon', 'StateCode': 'OR', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'OR04', 'ORG_UEI_NUM': 'Z3FGN9MF92U2', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF OREGON', 'ORG_PRNT_UEI_NUM': 'Z3FGN9MF92U2'}
|
{'Name': 'University of Oregon Eugene', 'CityName': 'EUGENE', 'StateCode': 'OR', 'ZipCode': '974031905', 'StreetAddress': '1776 E 13TH AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oregon', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'OR04'}
|
{'Code': '779600', 'Text': 'Algorithmic Foundations'}
|
2024~156058
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439255.xml'}
|
Collaborative Research: SaTC: CORE: Medium: Threat Intelligence for Targets of Coordinated Harassment
|
NSF
|
01/01/2024
|
10/31/2024
| 388,194 | 108,428 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Sara Kiesler', 'PO_EMAI': 'skiesler@nsf.gov', 'PO_PHON': '7032928643'}
|
Coordinated online harassment by collections of individuals and groups is a scourge of the modern Internet. It has upended and cost lives, silenced voices, and is making our public discourse more cruel and less representative. The phenomenon creates challenges for those who seek an equitable, secure and trustworthy internet to reduce the threat of coordinated attacks and handle attacks swiftly and effectively. Using the research team's past experiences with a clinical model that has been useful in helping victims of intimate partner violence, and new understandings of how to handle coordinated harassment to reduce harms and provide active assistance to targets of harassment, this project pilots an advice clinic. To ensure that the work has practical, real world impact, the project is also developing materials and working with platforms, threat intelligence companies, and non-profit organizations that help targets of online harassment .<br/><br/>The project uses a comprehensive set of technical and human-centered methods to advance our understanding of coordinated harassment threats and mitigation techniques. The coordination of harassment allows harassers to scale their attacks, but also provides defenders with an opportunity to monitor attackers. This project will study how threat intelligence---an emerging area of cybersecurity that has enabled the blocking, detecting, and remediation of cyberattacks---can be used to monitor channels where coordinated harassment and doxing campaigns happen, understand escalation processes, identify pain points, and prioritize courses of action for platforms, law enforcement, and targeted individuals. The multidisciplinary team and mixed methods approach will enable the project to not only build sophisticated tools, but also build scientific knowledge in multiple fields and to understand whether and how the proposed tools can contribute solutions to a complex societal problem.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/28/2024
|
07/28/2024
|
None
|
Grant
|
47.070, 47.075
|
1
|
4900
|
4900
|
2439312
|
{'FirstName': 'Andrea', 'LastName': 'Forte', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andrea Forte', 'EmailAddress': 'fortea@umich.edu', 'NSF_ID': '000561997', 'StartDate': '07/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'ZipCode': '481091079', 'PhoneNumber': '7347636438', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'MI06', 'ORG_UEI_NUM': 'GNJ7BBP73WE9', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MICHIGAN', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'StateCode': 'MI', 'ZipCode': '481091079', 'StreetAddress': 'ANN ARBOR, MI 481091079', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'MI06'}
|
{'Code': '806000', 'Text': 'Secure &Trustworthy Cyberspace'}
|
2020~108427
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439312.xml'}
|
Travel: NSF Student Travel Grant for 2024 ACM Conference on Emerging Networking EXperiments and Technologies
|
NSF
|
09/01/2024
|
08/31/2025
| 11,140 | 11,140 |
{'Value': 'Standard Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Ann Von Lehmen', 'PO_EMAI': 'avonlehm@nsf.gov', 'PO_PHON': '7032924756'}
|
This is a travel grant to support student travel to Co-NEXT 2024, to be held in Los Angeles, California.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/09/2024
|
08/09/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2439532
|
{'FirstName': 'Minmei', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Minmei Wang', 'EmailAddress': 'minmei.wang@uconn.edu', 'NSF_ID': '000918925', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Connecticut', 'CityName': 'STORRS', 'ZipCode': '062699018', 'PhoneNumber': '8604863622', 'StreetAddress': '438 WHITNEY RD EXTENSION UNIT 11', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Connecticut', 'StateCode': 'CT', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'CT02', 'ORG_UEI_NUM': 'WNTPS995QBM7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CONNECTICUT', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Connecticut', 'CityName': 'STORRS', 'StateCode': 'CT', 'ZipCode': '062699018', 'StreetAddress': '438 WHITNEY RD EXTENSION UNIT 1133', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Connecticut', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'CT02'}
|
{'Code': '736300', 'Text': 'Networking Technology and Syst'}
|
2024~11140
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439532.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 159,000 | 159,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Christopher L. Hill', 'PO_EMAI': 'chill@nsf.gov', 'PO_PHON': '7032928776'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439543
|
{'FirstName': 'John', 'LastName': 'Flynn', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'John Flynn', 'EmailAddress': 'jflynn@amnh.org', 'NSF_ID': '000518966', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'American Museum Natural History', 'CityName': 'NEW YORK', 'ZipCode': '100245102', 'PhoneNumber': '2127695975', 'StreetAddress': '200 CENTRAL PARK W', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NY12', 'ORG_UEI_NUM': 'MNJDKB4FXLM6', 'ORG_LGL_BUS_NAME': 'THE AMERICAN MUSEUM OF NATURAL HISTORY', 'ORG_PRNT_UEI_NUM': 'MNJDKB4FXLM6'}
|
{'Name': 'American Museum Natural History', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100245102', 'StreetAddress': '200 CENTRAL PARK W', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NY12'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~159000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439543.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 521,520 | 521,520 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Christopher L. Hill', 'PO_EMAI': 'chill@nsf.gov', 'PO_PHON': '7032928776'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439551
|
{'FirstName': 'Markus', 'LastName': 'Kemmelmeier', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Markus Kemmelmeier', 'EmailAddress': 'markusk@unr.edu', 'NSF_ID': '000498207', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Board of Regents, NSHE, obo University of Nevada, Reno', 'CityName': 'RENO', 'ZipCode': '895570001', 'PhoneNumber': '7757844040', 'StreetAddress': '1664 N VIRGINIA ST # 285', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Nevada', 'StateCode': 'NV', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'NV02', 'ORG_UEI_NUM': 'WLDGTNCFFJZ3', 'ORG_LGL_BUS_NAME': 'BOARD OF REGENTS OF THE NEVADA SYSTEM OF HIGHER ED', 'ORG_PRNT_UEI_NUM': 'WLDGTNCFFJZ3'}
|
{'Name': 'Board of Regents, NSHE, obo University of Nevada, Reno', 'CityName': 'Reno', 'StateCode': 'NV', 'ZipCode': '895570001', 'StreetAddress': '1664 N VIRGINIA ST # 285', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Nevada', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'NV02'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~521520
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439551.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 272,000 | 272,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439554
|
{'FirstName': 'Scott', 'LastName': 'Lowe', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Scott E Lowe', 'EmailAddress': 'ScottLowe@boisestate.edu', 'NSF_ID': '000509764', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Boise State University', 'CityName': 'BOISE', 'ZipCode': '837250001', 'PhoneNumber': '2084261574', 'StreetAddress': '1910 UNIVERSITY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Idaho', 'StateCode': 'ID', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'ID02', 'ORG_UEI_NUM': 'HYWTVM5HNFM3', 'ORG_LGL_BUS_NAME': 'BOISE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'HYWTVM5HNFM3'}
|
{'Name': 'Boise State University', 'CityName': 'BOISE', 'StateCode': 'ID', 'ZipCode': '837250001', 'StreetAddress': '1910 UNIVERSITY DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Idaho', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'ID02'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~272000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439554.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 2,373,800 | 2,373,800 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439559
|
{'FirstName': 'Thomas', 'LastName': 'Lewis', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thomas A Lewis', 'EmailAddress': 'Thomas_Lewis@brown.edu', 'NSF_ID': '000802481', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Brown University', 'CityName': 'PROVIDENCE', 'ZipCode': '029129100', 'PhoneNumber': '4018632777', 'StreetAddress': '1 PROSPECT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Rhode Island', 'StateCode': 'RI', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'RI01', 'ORG_UEI_NUM': 'E3FDXZ6TBHW3', 'ORG_LGL_BUS_NAME': 'BROWN UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'E3FDXZ6TBHW3'}
|
{'Name': 'Brown University', 'CityName': 'PROVIDENCE', 'StateCode': 'RI', 'ZipCode': '029129100', 'StreetAddress': '1 PROSPECT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Rhode Island', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'RI01'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~2373800
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439559.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 186,760 | 186,760 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Christopher L. Hill', 'PO_EMAI': 'chill@nsf.gov', 'PO_PHON': '7032928776'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/20/2024
|
08/20/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439563
|
{'FirstName': 'Teck Kah', 'LastName': 'Lim', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Teck Kah Lim', 'EmailAddress': 'limtk@drexel.edu', 'NSF_ID': '000263551', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Drexel University', 'CityName': 'PHILADELPHIA', 'ZipCode': '191042875', 'PhoneNumber': '2158956342', 'StreetAddress': '3141 CHESTNUT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'PA03', 'ORG_UEI_NUM': 'XF3XM9642N96', 'ORG_LGL_BUS_NAME': 'DREXEL UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Drexel University', 'CityName': 'PHILADELPHIA', 'StateCode': 'PA', 'ZipCode': '191042875', 'StreetAddress': '3141 CHESTNUT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'PA03'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~186760
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439563.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 1,260,314 | 1,260,314 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Christopher L. Hill', 'PO_EMAI': 'chill@nsf.gov', 'PO_PHON': '7032928776'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439564
|
{'FirstName': 'Kimberly', 'LastName': 'Jacob Arriola', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kimberly Jacob Arriola', 'EmailAddress': 'kjacoba@emory.edu', 'NSF_ID': '000863397', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Emory University', 'CityName': 'ATLANTA', 'ZipCode': '303221061', 'PhoneNumber': '4047272503', 'StreetAddress': '201 DOWMAN DR NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'S352L5PJLMP8', 'ORG_LGL_BUS_NAME': 'EMORY UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Emory University', 'CityName': 'ATLANTA', 'StateCode': 'GA', 'ZipCode': '303221061', 'StreetAddress': '201 DOWMAN DR NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'GA05'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~1260314
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439564.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 277,610 | 277,610 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/21/2024
|
08/21/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439567
|
{'FirstName': 'Andres', 'LastName': 'Gil', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andres G Gil', 'EmailAddress': 'gila@fiu.edu', 'NSF_ID': '000592918', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Florida International University', 'CityName': 'MIAMI', 'ZipCode': '331992516', 'PhoneNumber': '3053482494', 'StreetAddress': '11200 SW 8TH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_ORG': 'FL26', 'ORG_UEI_NUM': 'Q3KCVK5S9CP1', 'ORG_LGL_BUS_NAME': 'FLORIDA INTERNATIONAL UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'Q3KCVK5S9CP1'}
|
{'Name': 'Florida International University', 'CityName': 'MIAMI', 'StateCode': 'FL', 'ZipCode': '331992516', 'StreetAddress': '11200 SW 8TH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_PERF': 'FL26'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~277610
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439567.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 265,000 | 265,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Christopher L. Hill', 'PO_EMAI': 'chill@nsf.gov', 'PO_PHON': '7032928776'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/20/2024
|
08/20/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439568
|
{'FirstName': 'Maria', 'LastName': 'Snyder', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Maria F Snyder', 'EmailAddress': 'mfs22@georgetown.edu', 'NSF_ID': '000099279', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Georgetown University', 'CityName': 'WASHINGTON', 'ZipCode': '200570001', 'PhoneNumber': '2026250100', 'StreetAddress': 'MAIN CAMPUS', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'District of Columbia', 'StateCode': 'DC', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DC00', 'ORG_UEI_NUM': 'TF2CMKY1HMX9', 'ORG_LGL_BUS_NAME': 'GEORGETOWN UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'TF2CMKY1HMX9'}
|
{'Name': 'Georgetown University', 'CityName': 'WASHINGTON', 'StateCode': 'DC', 'ZipCode': '200570001', 'StreetAddress': 'MAIN CAMPUS', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'District of Columbia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DC00'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~265000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439568.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 159,000 | 159,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439577
|
{'FirstName': 'Rhea', 'LastName': 'Williamson', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rhea Williamson', 'EmailAddress': 'rwilliam@email.sjsu.edu', 'NSF_ID': '000258891', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Humboldt State University Foundation', 'CityName': 'ARCATA', 'ZipCode': '955218222', 'PhoneNumber': '7078264189', 'StreetAddress': '1 HARPST ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'CA02', 'ORG_UEI_NUM': 'K1S8M8RU4FK7', 'ORG_LGL_BUS_NAME': 'CAL POLY HUMBOLDT SPONSORED PROGRAMS FOUNDATION', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Humboldt State University Foundation', 'CityName': 'ARCATA', 'StateCode': 'CA', 'ZipCode': '955218222', 'StreetAddress': '1 HARPST ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'CA02'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~159000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439577.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 212,000 | 212,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439583
|
{'FirstName': 'Michael', 'LastName': 'Crowder', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael W Crowder', 'EmailAddress': 'crowdemw@muohio.edu', 'NSF_ID': '000243337', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Miami University', 'CityName': 'OXFORD', 'ZipCode': '450561846', 'PhoneNumber': '5135293600', 'StreetAddress': '501 E HIGH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_ORG': 'OH08', 'ORG_UEI_NUM': 'T6J6AF3AM8M8', 'ORG_LGL_BUS_NAME': 'MIAMI UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Miami University', 'CityName': 'OXFORD', 'StateCode': 'OH', 'ZipCode': '450561846', 'StreetAddress': '501 E HIGH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_PERF': 'OH08'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~212000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439583.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 53,000 | 53,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/20/2024
|
08/20/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439588
|
{'FirstName': 'Amy', 'LastName': 'Levin', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Amy C Levin', 'EmailAddress': 'amy.levin@csun.edu', 'NSF_ID': '000783255', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'The University Corporation, Northridge', 'CityName': 'NORTHRIDGE', 'ZipCode': '913300001', 'PhoneNumber': '8186771403', 'StreetAddress': '18111 NORDHOFF ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '32', 'CONGRESS_DISTRICT_ORG': 'CA32', 'ORG_UEI_NUM': 'LAGNHMC58DF3', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY CORPORATION', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'The University Corporation, Northridge', 'CityName': 'NORTHRIDGE', 'StateCode': 'CA', 'ZipCode': '913300001', 'StreetAddress': '18111 NORDHOFF ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '32', 'CONGRESS_DISTRICT_PERF': 'CA32'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~53000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439588.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 53,000 | 53,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439595
|
{'FirstName': 'Alice', 'LastName': 'Camuti', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alice K Camuti', 'EmailAddress': 'acamuti@tntech.edu', 'NSF_ID': '000785305', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Tennessee Technological University', 'CityName': 'COOKEVILLE', 'ZipCode': '385050001', 'PhoneNumber': '9313723374', 'StreetAddress': '1 WILLIAM L JONES DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Tennessee', 'StateCode': 'TN', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'TN06', 'ORG_UEI_NUM': 'KZNHNMDUTJA5', 'ORG_LGL_BUS_NAME': 'TENNESSEE TECHNOLOGICAL UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Tennessee Technological University', 'CityName': 'COOKEVILLE', 'StateCode': 'TN', 'ZipCode': '385050001', 'StreetAddress': '1 WILLIAM L JONES DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Tennessee', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'TN06'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~53000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439595.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 184,417 | 184,417 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439598
|
{'FirstName': 'Robin', 'LastName': 'Poston', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robin Poston', 'EmailAddress': 'rposton@smu.edu', 'NSF_ID': '000942989', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Southern Methodist University', 'CityName': 'DALLAS', 'ZipCode': '752051902', 'PhoneNumber': '2147684708', 'StreetAddress': '6425 BOAZ ST RM 130', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_ORG': 'TX24', 'ORG_UEI_NUM': 'D33QGS3Q3DJ3', 'ORG_LGL_BUS_NAME': 'SOUTHERN METHODIST UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'S88YPE3BLV66'}
|
{'Name': 'Southern Methodist University', 'CityName': 'DALLAS', 'StateCode': 'TX', 'ZipCode': '752051902', 'StreetAddress': '6425 BOAZ ST RM 130', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_PERF': 'TX24'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~184417
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439598.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 53,000 | 53,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439601
|
{'FirstName': 'Matthias', 'LastName': 'Beck', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Matthias Beck', 'EmailAddress': 'mattbeck@sfsu.edu', 'NSF_ID': '000204681', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'San Francisco State University', 'CityName': 'SAN FRANCISCO', 'ZipCode': '941321740', 'PhoneNumber': '4153387090', 'StreetAddress': '1600 HOLLOWAY AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'CA11', 'ORG_UEI_NUM': 'F4SLJ5WF59F6', 'ORG_LGL_BUS_NAME': 'SAN FRANCISCO STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'NUDGYLBB4S99'}
|
{'Name': 'San Francisco State University', 'CityName': 'SAN FRANCISCO', 'StateCode': 'CA', 'ZipCode': '941321740', 'StreetAddress': '1600 HOLLOWAY AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'CA11'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~53000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439601.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 546,800 | 546,800 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439608
|
{'FirstName': 'Emily', 'LastName': 'Harms', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Emily B Harms', 'EmailAddress': 'harmse@rockefeller.edu', 'NSF_ID': '000401104', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Rockefeller University', 'CityName': 'NEW YORK', 'ZipCode': '100656399', 'PhoneNumber': '2123278309', 'StreetAddress': '1230 YORK AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NY12', 'ORG_UEI_NUM': 'LHGDNJMZ64Y1', 'ORG_LGL_BUS_NAME': 'ROCKEFELLER UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Rockefeller University', 'CityName': 'New York', 'StateCode': 'NY', 'ZipCode': '100656399', 'StreetAddress': '1230 YORK AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NY12'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~546800
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439608.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 202,750 | 202,750 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439611
|
{'FirstName': 'Dana', 'LastName': 'Director', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dana Director', 'EmailAddress': 'director@ohsu.edu', 'NSF_ID': '000771382', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Oregon Health & Science University', 'CityName': 'PORTLAND', 'ZipCode': '972393011', 'PhoneNumber': '5034947784', 'StreetAddress': '3181 SW SAM JACKSON PARK RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oregon', 'StateCode': 'OR', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'OR01', 'ORG_UEI_NUM': 'NPSNT86JKN51', 'ORG_LGL_BUS_NAME': 'OREGON HEALTH & SCIENCE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Oregon Health & Science University', 'CityName': 'PORTLAND', 'StateCode': 'OR', 'ZipCode': '972393011', 'StreetAddress': '3181 SW SAM JACKSON PARK RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oregon', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'OR01'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~202750
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439611.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 453,040 | 453,040 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439612
|
{'FirstName': 'Mary', 'LastName': 'Watwood', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mary E Watwood', 'EmailAddress': 'maribeth.watwood@nau.edu', 'NSF_ID': '000261866', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Northern Arizona University', 'CityName': 'FLAGSTAFF', 'ZipCode': '86011', 'PhoneNumber': '9285230886', 'StreetAddress': '601 S KNOLES DR RM 220', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Arizona', 'StateCode': 'AZ', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'AZ02', 'ORG_UEI_NUM': 'MXHAS3AKPRN1', 'ORG_LGL_BUS_NAME': 'NORTHERN ARIZONA UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Northern Arizona University', 'CityName': 'FLAGSTAFF', 'StateCode': 'AZ', 'ZipCode': '860015665', 'StreetAddress': '601 S KNOLES DR RM 220', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arizona', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'AZ02'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~453040
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439612.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 185,250 | 185,250 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439621
|
{'FirstName': 'Naoko', 'LastName': 'Tanese', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Naoko Tanese', 'EmailAddress': 'tanesn01@med.nyu.edu', 'NSF_ID': '000260497', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'New York University Medical Center', 'CityName': 'NEW YORK', 'ZipCode': '100166402', 'PhoneNumber': '2122638822', 'StreetAddress': '550 1ST AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NY12', 'ORG_UEI_NUM': 'M5SZJ6VHUHN8', 'ORG_LGL_BUS_NAME': 'NEW YORK UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'New York University Medical Center', 'CityName': 'New York', 'StateCode': 'NY', 'ZipCode': '100166402', 'StreetAddress': '550 1ST AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NY12'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~185250
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439621.xml'}
|
Collaborative Research: RAPID: Quantifying the fluvial geomorphic response of the Blue Earth River to a catastrophic avulsive dam failure, Rapidan Dam, Minnesota
|
NSF
|
08/15/2024
|
07/31/2025
| 17,957 | 17,957 |
{'Value': 'Standard Grant'}
|
{'Code': '06030000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'EAR', 'LongName': 'Division Of Earth Sciences'}}
|
{'SignBlockName': 'Justin Lawrence', 'PO_EMAI': 'jlawrenc@nsf.gov', 'PO_PHON': '7032922425'}
|
After three days (17–20 cm) of rainfall flooded the Blue Earth River, the river avulsed around the western edge of the ~114 year old Rapidan Dam in the early morning of 24 June 2024. Rapid incision and lateral migration shifted the bank ~100 m westward in three days. This event, which the investigators have termed an “avulsive dam failure”, provides a brief time window to study the fundamental coupled fluvial and hillslope processes that result from rapid base-level fall, including knickpoint development and retreat coupled with lateral erosion alongside mass-wasting processes associated with sudden valley incision. Climate and land-use change combine to generate larger floods whose erosion then destabilizes the surrounding landscape, thereby producing cascading hazards. The investigators hypothesize that rapid incision and channel migration should immediately follow avulsive dam failure, similarly to basin integration following spillover when a new hydrogeomorphic system is established after breaching a sill. This is followed by relaxation of the river’s longitudinal profile as knickpoints evolve and the river adjusts to a new local base level. The investigators will capture and analyze these geomorphic phenomena through time with repeated collection of unmanned aerial systems (UAS) imagery, supplemented by community-collected data. They will quantify volumes of erosion and deposition, flow velocities, and channel-migration rates using data products derived from structure-from-motion photogrammetry and aerial footage. Aging dam infrastructure across the United States, combined with increased magnitude and frequency of precipitation, will likely drive continued dam failures into the future. The data resulting from this work could inform future management strategies, especially as our national dam infrastructure continues to age. This project will provide high-impact research experiences for both undergraduate and graduate students, while serving to mentor them under a collaborative, multi-institutional environment with broad expertise in geospatial and geoscientific disciplines.<br/><br/>Rapid data collection following this avulsive dam failure will help to answer core geomorphic questions about basin integration and subsequent knickzone evolution. Physical models demonstrate that much of the incision from spillover processes occurs during and shortly after the event. Attempts to quantify these changes in a real-world setting must effectively capture these early stages that record the most rapid change within the fluvial system. Additionally, longer-term data will capture knickpoint-retreat rates, including whether the knickpoint remains coherent or diffuses, across stratigraphic units with varied mechanical properties (that is, glacial lake sediments to sandstone bedrock). Over the shorter term, the results of this project may help to explain and predict rapid bluff retreat along the Blue Earth and other rivers, attributed to anthropogenic climate and land-use change. Furthermore, the investigators will quantify downstream sediment dynamics in response to erosion and mobilization of reservoir deposits.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/09/2024
|
08/09/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2439622
|
{'FirstName': 'Zach', 'LastName': 'Hilgendorf', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zach Hilgendorf', 'EmailAddress': 'hilgenzt@uwec.edu', 'NSF_ID': '0000A0HQR', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Wisconsin-Eau Claire', 'CityName': 'EAU CLAIRE', 'ZipCode': '547014811', 'PhoneNumber': '7158363405', 'StreetAddress': '105 GARFIELD AVENUE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'WI03', 'ORG_UEI_NUM': 'RYAQZNSJN9Q9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WISCONSIN SYSTEM', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Wisconsin-Eau Claire', 'CityName': 'EAU CLAIRE', 'StateCode': 'WI', 'ZipCode': '547014811', 'StreetAddress': '105 GARFIELD AVENUE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'WI03'}
|
[{'Code': '722200', 'Text': 'XC-Crosscutting Activities Pro'}, {'Code': '745800', 'Text': 'Geomorphology & Land-use Dynam'}]
|
2024~17957
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439622.xml'}
|
Collaborative Research: RAPID: Quantifying the fluvial geomorphic response of the Blue Earth River to a catastrophic avulsive dam failure, Rapidan Dam, Minnesota
|
NSF
|
08/15/2024
|
07/31/2025
| 5,036 | 5,036 |
{'Value': 'Standard Grant'}
|
{'Code': '06030000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'EAR', 'LongName': 'Division Of Earth Sciences'}}
|
{'SignBlockName': 'Justin Lawrence', 'PO_EMAI': 'jlawrenc@nsf.gov', 'PO_PHON': '7032922425'}
|
After three days (17–20 cm) of rainfall flooded the Blue Earth River, the river avulsed around the western edge of the ~114 year old Rapidan Dam in the early morning of 24 June 2024. Rapid incision and lateral migration shifted the bank ~100 m westward in three days. This event, which the investigators have termed an “avulsive dam failure”, provides a brief time window to study the fundamental coupled fluvial and hillslope processes that result from rapid base-level fall, including knickpoint development and retreat coupled with lateral erosion alongside mass-wasting processes associated with sudden valley incision. Climate and land-use change combine to generate larger floods whose erosion then destabilizes the surrounding landscape, thereby producing cascading hazards. The investigators hypothesize that rapid incision and channel migration should immediately follow avulsive dam failure, similarly to basin integration following spillover when a new hydrogeomorphic system is established after breaching a sill. This is followed by relaxation of the river’s longitudinal profile as knickpoints evolve and the river adjusts to a new local base level. The investigators will capture and analyze these geomorphic phenomena through time with repeated collection of unmanned aerial systems (UAS) imagery, supplemented by community-collected data. They will quantify volumes of erosion and deposition, flow velocities, and channel-migration rates using data products derived from structure-from-motion photogrammetry and aerial footage. Aging dam infrastructure across the United States, combined with increased magnitude and frequency of precipitation, will likely drive continued dam failures into the future. The data resulting from this work could inform future management strategies, especially as our national dam infrastructure continues to age. This project will provide high-impact research experiences for both undergraduate and graduate students, while serving to mentor them under a collaborative, multi-institutional environment with broad expertise in geospatial and geoscientific disciplines.<br/><br/>Rapid data collection following this avulsive dam failure will help to answer core geomorphic questions about basin integration and subsequent knickzone evolution. Physical models demonstrate that much of the incision from spillover processes occurs during and shortly after the event. Attempts to quantify these changes in a real-world setting must effectively capture these early stages that record the most rapid change within the fluvial system. Additionally, longer-term data will capture knickpoint-retreat rates, including whether the knickpoint remains coherent or diffuses, across stratigraphic units with varied mechanical properties (that is, glacial lake sediments to sandstone bedrock). Over the shorter term, the results of this project may help to explain and predict rapid bluff retreat along the Blue Earth and other rivers, attributed to anthropogenic climate and land-use change. Furthermore, the investigators will quantify downstream sediment dynamics in response to erosion and mobilization of reservoir deposits.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/09/2024
|
08/09/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2439623
|
{'FirstName': 'Andrew', 'LastName': 'Wickert', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andrew D Wickert', 'EmailAddress': 'awickert@umn.edu', 'NSF_ID': '000733915', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'ZipCode': '554552009', 'PhoneNumber': '6126245599', 'StreetAddress': '200 OAK ST SE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Minnesota', 'StateCode': 'MN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MN05', 'ORG_UEI_NUM': 'KABJZBBJ4B54', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MINNESOTA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'StateCode': 'MN', 'ZipCode': '554552009', 'StreetAddress': '116 Church St SE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Minnesota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MN05'}
|
[{'Code': '722200', 'Text': 'XC-Crosscutting Activities Pro'}, {'Code': '745800', 'Text': 'Geomorphology & Land-use Dynam'}]
|
2024~5036
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439623.xml'}
|
Collaborative Research: RAPID: Quantifying the fluvial geomorphic response of the Blue Earth River to a catastrophic avulsive dam failure, Rapidan Dam, Minnesota
|
NSF
|
08/15/2024
|
07/31/2025
| 26,558 | 26,558 |
{'Value': 'Standard Grant'}
|
{'Code': '06030000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'EAR', 'LongName': 'Division Of Earth Sciences'}}
|
{'SignBlockName': 'Justin Lawrence', 'PO_EMAI': 'jlawrenc@nsf.gov', 'PO_PHON': '7032922425'}
|
After three days (17–20 cm) of rainfall flooded the Blue Earth River, the river avulsed around the western edge of the ~114 year old Rapidan Dam in the early morning of 24 June 2024. Rapid incision and lateral migration shifted the bank ~100 m westward in three days. This event, which the investigators have termed an “avulsive dam failure”, provides a brief time window to study the fundamental coupled fluvial and hillslope processes that result from rapid base-level fall, including knickpoint development and retreat coupled with lateral erosion alongside mass-wasting processes associated with sudden valley incision. Climate and land-use change combine to generate larger floods whose erosion then destabilizes the surrounding landscape, thereby producing cascading hazards. The investigators hypothesize that rapid incision and channel migration should immediately follow avulsive dam failure, similarly to basin integration following spillover when a new hydrogeomorphic system is established after breaching a sill. This is followed by relaxation of the river’s longitudinal profile as knickpoints evolve and the river adjusts to a new local base level. The investigators will capture and analyze these geomorphic phenomena through time with repeated collection of unmanned aerial systems (UAS) imagery, supplemented by community-collected data. They will quantify volumes of erosion and deposition, flow velocities, and channel-migration rates using data products derived from structure-from-motion photogrammetry and aerial footage. Aging dam infrastructure across the United States, combined with increased magnitude and frequency of precipitation, will likely drive continued dam failures into the future. The data resulting from this work could inform future management strategies, especially as our national dam infrastructure continues to age. This project will provide high-impact research experiences for both undergraduate and graduate students, while serving to mentor them under a collaborative, multi-institutional environment with broad expertise in geospatial and geoscientific disciplines.<br/><br/>Rapid data collection following this avulsive dam failure will help to answer core geomorphic questions about basin integration and subsequent knickzone evolution. Physical models demonstrate that much of the incision from spillover processes occurs during and shortly after the event. Attempts to quantify these changes in a real-world setting must effectively capture these early stages that record the most rapid change within the fluvial system. Additionally, longer-term data will capture knickpoint-retreat rates, including whether the knickpoint remains coherent or diffuses, across stratigraphic units with varied mechanical properties (that is, glacial lake sediments to sandstone bedrock). Over the shorter term, the results of this project may help to explain and predict rapid bluff retreat along the Blue Earth and other rivers, attributed to anthropogenic climate and land-use change. Furthermore, the investigators will quantify downstream sediment dynamics in response to erosion and mobilization of reservoir deposits.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/09/2024
|
08/09/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2439624
|
{'FirstName': 'Phillip', 'LastName': 'Larson', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Phillip Larson', 'EmailAddress': 'phillip.larson@mnsu.edu', 'NSF_ID': '000727701', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Minnesota State University, Mankato', 'CityName': 'MANKATO', 'ZipCode': '560016067', 'PhoneNumber': '5073895275', 'StreetAddress': '236 WIGLEY ADMINISTRATION CTR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Minnesota', 'StateCode': 'MN', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'MN01', 'ORG_UEI_NUM': 'R5YNEHC2NA98', 'ORG_LGL_BUS_NAME': 'MINNESOTA STATE UNIVERSITY MANKATO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Minnesota State University, Mankato', 'CityName': 'MANKATO', 'StateCode': 'MN', 'ZipCode': '560016067', 'StreetAddress': '236 WIGLEY ADMINISTRATION CTR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Minnesota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'MN01'}
|
[{'Code': '722200', 'Text': 'XC-Crosscutting Activities Pro'}, {'Code': '745800', 'Text': 'Geomorphology & Land-use Dynam'}]
|
2024~26558
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439624.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 371,000 | 371,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439625
|
{'FirstName': 'Craig', 'LastName': 'Ogilvie', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Craig A Ogilvie', 'EmailAddress': 'craig.ogilvie@montana.edu', 'NSF_ID': '000324510', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Montana State University', 'CityName': 'BOZEMAN', 'ZipCode': '59717', 'PhoneNumber': '4069942381', 'StreetAddress': '216 MONTANA HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Montana', 'StateCode': 'MT', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'MT01', 'ORG_UEI_NUM': 'EJ3UF7TK8RT5', 'ORG_LGL_BUS_NAME': 'MONTANA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Montana State University', 'CityName': 'BOZEMAN', 'StateCode': 'MT', 'ZipCode': '597155065', 'StreetAddress': '103 CULBERTSON HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Montana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'MT01'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~371000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439625.xml'}
|
Travel: GENETIS and Nebulous Meeting on Developing the use of AI for Design of scientific Instruments
|
NSF
|
08/01/2024
|
07/31/2025
| 21,888 | 21,888 |
{'Value': 'Standard Grant'}
|
{'Code': '03010000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'PHY', 'LongName': 'Division Of Physics'}}
|
{'SignBlockName': 'Nigel Sharp', 'PO_EMAI': 'nsharp@nsf.gov', 'PO_PHON': '7032924905'}
|
The GENETIS and Nebulous projects aim to provide a nexus point for collaborations from astrophysics, other areas of science, and industry to design instruments for optimal scientific outcomes that may not be achievable with human engineering. Initially, they have focused on genetic algorithms and have already evolved antennas for neutrino astrophysics applications. This group travel award supports attendance by team members at a “Blue Sky Studies” workshop and follow-up GENETIS meeting to be held at CalTech in Pasadena, CA, August 12-14. The goal of this workshop is to develop a plan for broadening and streamlining the use of AI for the design of instruments, with a focus on applications in astrophysics. By standardizing tools developed by the GENETIS and Nebulous projects, the expectation is that the design phase of experiments will become more efficient, while also increasing scientific impact. The meeting will create a prioritized roadmap for developing AI for instrument design, understanding the needs of future missions and experiments, and the limitations of AI. GENETIS has an exemplary record as a launch pad for diverse undergraduate and graduate students, including those from minority-serving institutions. This interdisciplinary team adds new perspectives to every aspect of the work and provides rich learning opportunities for early career researchers.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2439689
|
{'FirstName': 'Amy', 'LastName': 'Connolly', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Amy L Connolly', 'EmailAddress': 'connolly@physics.osu.edu', 'NSF_ID': '000575262', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'ZipCode': '432101016', 'PhoneNumber': '6146888735', 'StreetAddress': '1960 KENNY RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'OH03', 'ORG_UEI_NUM': 'DLWBSLWAJWR1', 'ORG_LGL_BUS_NAME': 'OHIO STATE UNIVERSITY, THE', 'ORG_PRNT_UEI_NUM': 'MN4MDDMN8529'}
|
{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'StateCode': 'OH', 'ZipCode': '432101016', 'StreetAddress': '1960 KENNY RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'OH03'}
|
{'Code': '164300', 'Text': 'Particle Astrophysics/Cosmic P'}
|
2024~21888
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439689.xml'}
|
Collaborative Research: EAGER: End-to-end Neural Training for Very Large Output Spaces
|
NSF
|
08/15/2024
|
07/31/2026
| 75,000 | 75,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
|
{'SignBlockName': 'Raj Acharya', 'PO_EMAI': 'racharya@nsf.gov', 'PO_PHON': '7032927978'}
|
Modern machine learning models often need to make predictions with an enormous amount of choices. For example, on the internet, search engines need to predict the most relevant candidate for a given query from billions of potential candidates. There are similar prediction problems that are ubiquitous in many search, retrieval and recommendation systems in our daily lives. It is challenging for a machine learning algorithm to deal with a large output space in both the training and inference phases, as any linear scan through all candidates is computationally prohibitive. This project aims to develop a family of scalable and reliable algorithms to tackle the problem of predicting in a large output space. To develop an end-to-end solution, we will tackle the problem of designing novel architectures, and accompanying training and inference procedures that jointly optimize inference speed and prediction accuracy. These efforts will eventually produce a comprehensive toolkit for learning with large output spaces, thus enabling its application in both practical systems and future research activities. The project will also support students and train them in conducting research activities in collaboration with application domains.<br/><br/>Existing approaches for dealing with a large output space split the prediction task into two separate components: a neural network encoder and an approximate nearest neighbor search module. The neural network encoder encodes queries and items into a latent space, while the nearest neighbor search module finds the closest vectors in the database for a given query vector. This two-stage approach simplifies the development of each module, but this splitting of components is not focused on end-to-end prediction performance, and thus compromises accuracy and efficiency. The core challenging technical direction of this project is to create algorithms that allow the two components to be aware of each other and thus develop an end-to-end model and training algorithm to handle very large output space. This research direction will be addressed through the development of a novel end-to-end neural network architecture that contains both encoders and trainable search modules. The end-to-end training process will enable direct optimization for precision and efficiency in a single step, instead of requiring two separate steps.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2439754
|
{'FirstName': 'Inderjit', 'LastName': 'Dhillon', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Inderjit S Dhillon', 'EmailAddress': 'inderjit@cs.utexas.edu', 'NSF_ID': '000200521', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Texas at Austin', 'CityName': 'AUSTIN', 'ZipCode': '787121139', 'PhoneNumber': '5124716424', 'StreetAddress': '110 INNER CAMPUS DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'TX25', 'ORG_UEI_NUM': 'V6AFQPN18437', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TEXAS AT AUSTIN', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Texas at Austin', 'CityName': 'AUSTIN', 'StateCode': 'TX', 'ZipCode': '787121139', 'StreetAddress': '110 INNER CAMPUS DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'TX25'}
|
{'Code': '736400', 'Text': 'Info Integration & Informatics'}
|
2024~75000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439754.xml'}
|
Collaborative Research: EAGER: End-to-end Neural Training for Very Large Output Spaces
|
NSF
|
08/15/2024
|
07/31/2026
| 25,000 | 25,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
|
{'SignBlockName': 'Raj Acharya', 'PO_EMAI': 'racharya@nsf.gov', 'PO_PHON': '7032927978'}
|
Modern machine learning models often need to make predictions with an enormous amount of choices. For example, on the internet, search engines need to predict the most relevant candidate for a given query from billions of potential candidates. There are similar prediction problems that are ubiquitous in many search, retrieval and recommendation systems in our daily lives. It is challenging for a machine learning algorithm to deal with a large output space in both the training and inference phases, as any linear scan through all candidates is computationally prohibitive. This project aims to develop a family of scalable and reliable algorithms to tackle the problem of predicting in a large output space. To develop an end-to-end solution, we will tackle the problem of designing novel architectures, and accompanying training and inference procedures that jointly optimize inference speed and prediction accuracy. These efforts will eventually produce a comprehensive toolkit for learning with large output spaces, thus enabling its application in both practical systems and future research activities. The project will also support students and train them in conducting research activities in collaboration with application domains.<br/><br/>Existing approaches for dealing with a large output space split the prediction task into two separate components: a neural network encoder and an approximate nearest neighbor search module. The neural network encoder encodes queries and items into a latent space, while the nearest neighbor search module finds the closest vectors in the database for a given query vector. This two-stage approach simplifies the development of each module, but this splitting of components is not focused on end-to-end prediction performance, and thus compromises accuracy and efficiency. The core challenging technical direction of this project is to create algorithms that allow the two components to be aware of each other and thus develop an end-to-end model and training algorithm to handle very large output space. This research direction will be addressed through the development of a novel end-to-end neural network architecture that contains both encoders and trainable search modules. The end-to-end training process will enable direct optimization for precision and efficiency in a single step, instead of requiring two separate steps.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/19/2024
|
08/19/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2439755
|
{'FirstName': 'Cho-Jui', 'LastName': 'Hsieh', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Cho-Jui Hsieh', 'EmailAddress': 'chohsieh@cs.ucla.edu', 'NSF_ID': '000711637', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-Los Angeles', 'CityName': 'LOS ANGELES', 'ZipCode': '900244200', 'PhoneNumber': '3107940102', 'StreetAddress': '10889 WILSHIRE BLVD STE 700', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '36', 'CONGRESS_DISTRICT_ORG': 'CA36', 'ORG_UEI_NUM': 'RN64EPNH8JC6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, LOS ANGELES', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'UCLA Compter Science', 'CityName': 'Los Angeles', 'StateCode': 'CA', 'ZipCode': '900951596', 'StreetAddress': '404 Westwood Plaza', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '36', 'CONGRESS_DISTRICT_PERF': 'CA36'}
|
{'Code': '736400', 'Text': 'Info Integration & Informatics'}
|
2024~25000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439755.xml'}
|
Conference: 15th International Conference for Invertebrate Reproduction & Development
|
NSF
|
09/01/2024
|
08/31/2025
| 20,000 | 20,000 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Anna Allen', 'PO_EMAI': 'akallen@nsf.gov', 'PO_PHON': '7032928011'}
|
Since 1975, the triennial International Congress of Invertebrate Reproduction and Development (ICIRD) has showcased high-quality research across the entire breadth of animal life. This conference is highly integrated along several dimensions, as it brings together biologists from many nations and institution types who are conducting research on many different invertebrate animal species. Further, their research examines reproduction and development at diverse biological levels, from ecological context to the roles of individual genes. This award supports the resumption of the ICIRD series, after the scheduled 15th Congress was cancelled due to the COVID-19 pandemic. More specifically, the award will support the attendance of 14 US researchers at different career stages at the Congress, to be held June 6-10, 2025 in Washington, DC. This meeting presents an excellent opportunity to support early career trainees in the field of invertebrate reproductive biology to network and learn about the exciting new advances in the field. The Broader Impacts of the conference include the support of early career researchers and the advancement of research programs. <br/><br/>The International Congress of Invertebrate Reproduction and Development (ICIRD) is a conference that takes a unique pan-metazoan view of reproduction, with a focus on less-studied taxa. Scientific topics to be covered at the conference include, but are not limited to: regeneration/body maintenance/asexual reproduction, invertebrates as food, evo-devo of reproductive mechanisms, gametogenesis and fertilization, evolution, genomic and genetic tools for pan-metazoan reproductive biology, larval development, and metamorphosis. By bringing together diverse researchers who work on many different animal phyla at several biological levels, broad patterns will appear that are not likely to emerge in conferences focused on a single taxon or level of organization. This award will be utilized to defray the costs for early career researchers (early-career PIs, post-doctoral fellows and student trainees) to attend and participate in the Congress.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2439773
|
{'FirstName': 'Eric', 'LastName': 'Haag', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eric S Haag', 'EmailAddress': 'ehaag@umd.edu', 'NSF_ID': '000426639', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'ZipCode': '207425100', 'PhoneNumber': '3014056269', 'StreetAddress': '3112 LEE BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MD04', 'ORG_UEI_NUM': 'NPU8ULVAAS23', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, COLLEGE PARK', 'ORG_PRNT_UEI_NUM': 'NPU8ULVAAS23'}
|
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'StateCode': 'MD', 'ZipCode': '207425100', 'StreetAddress': '3112 LEE BUILDING', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MD04'}
|
{'Code': '111900', 'Text': 'Animal Developmental Mechanism'}
|
2024~20000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439773.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 53,000 | 53,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439840
|
{'FirstName': 'Susan', 'LastName': 'Carvalho', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Susan Carvalho', 'EmailAddress': 'secarvalho@ua.edu', 'NSF_ID': '000673869', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Alabama Tuscaloosa', 'CityName': 'TUSCALOOSA', 'ZipCode': '354012029', 'PhoneNumber': '2053485152', 'StreetAddress': '801 UNIVERSITY BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Alabama', 'StateCode': 'AL', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'AL07', 'ORG_UEI_NUM': 'RCNJEHZ83EV6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ALABAMA', 'ORG_PRNT_UEI_NUM': 'TWJWHYEM8T63'}
|
{'Name': 'University of Alabama Tuscaloosa', 'CityName': 'TUSCALOOSA', 'StateCode': 'AL', 'ZipCode': '354012029', 'StreetAddress': '801 UNIVERSITY BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Alabama', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'AL07'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~53000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439840.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 4,882,666 | 4,882,666 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439841
|
{'FirstName': 'Edward', 'LastName': 'Adler', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Edward S Adler', 'EmailAddress': 'E.Scott.Adler@colorado.edu', 'NSF_ID': '000323255', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Colorado at Boulder', 'CityName': 'Boulder', 'ZipCode': '803090001', 'PhoneNumber': '3034926221', 'StreetAddress': '3100 MARINE ST', 'StreetAddress2': 'STE 481 572 UCB', 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'CO02', 'ORG_UEI_NUM': 'SPVKK1RC2MZ3', 'ORG_LGL_BUS_NAME': 'THE REGENTS OF THE UNIVERSITY OF COLORADO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Colorado at Boulder', 'CityName': 'Boulder', 'StateCode': 'CO', 'ZipCode': '803090001', 'StreetAddress': '3100 MARINE ST STE 481 572 UCB', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'CO02'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~4882666
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439841.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 159,000 | 159,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439843
|
{'FirstName': 'Sandra', 'LastName': 'Eaton', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sandra S Eaton', 'EmailAddress': 'seaton@du.edu', 'NSF_ID': '000098978', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Denver', 'CityName': 'DENVER', 'ZipCode': '802104711', 'PhoneNumber': '3038712000', 'StreetAddress': '2199 S UNIVERSITY BLVD RM 222', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'CO01', 'ORG_UEI_NUM': 'WCUGNQQ8DZU1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF DENVER', 'ORG_PRNT_UEI_NUM': 'WCUGNQQ8DZU1'}
|
{'Name': 'University of Denver', 'CityName': 'DENVER', 'StateCode': 'CO', 'ZipCode': '802104711', 'StreetAddress': '2199 S UNIVERSITY BLVD RM 222', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'CO01'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~159000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439843.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 211,000 | 211,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439844
|
{'FirstName': 'Amanda', 'LastName': 'Thein', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Amanda H Thein', 'EmailAddress': 'amanda-haertling-thein@uiowa.edu', 'NSF_ID': '000861380', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Iowa', 'CityName': 'IOWA CITY', 'ZipCode': '522421316', 'PhoneNumber': '3193352123', 'StreetAddress': '105 JESSUP HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Iowa', 'StateCode': 'IA', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'IA01', 'ORG_UEI_NUM': 'Z1H9VJS8NG16', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF IOWA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Iowa', 'CityName': 'IOWA CITY', 'StateCode': 'IA', 'ZipCode': '522421316', 'StreetAddress': '105 JESSUP HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Iowa', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'IA01'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~211000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439844.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 570,040 | 570,040 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439845
|
{'FirstName': 'Jennifer', 'LastName': 'Roberts', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jennifer A Roberts', 'EmailAddress': 'jaroberts@ku.edu', 'NSF_ID': '000420435', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Kansas Center for Research Inc', 'CityName': 'LAWRENCE', 'ZipCode': '660457563', 'PhoneNumber': '7858643441', 'StreetAddress': '2385 IRVING HILL RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Kansas', 'StateCode': 'KS', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'KS01', 'ORG_UEI_NUM': 'SSUJB3GSH8A5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF KANSAS CENTER FOR RESEARCH INC', 'ORG_PRNT_UEI_NUM': 'SSUJB3GSH8A5'}
|
{'Name': 'University of Kansas Center for Research Inc', 'CityName': 'LAWRENCE', 'StateCode': 'KS', 'ZipCode': '660457563', 'StreetAddress': '2385 IRVING HILL RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Kansas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'KS01'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~570040
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439845.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 712,840 | 712,840 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439846
|
{'FirstName': 'Jacqueline', 'LastName': 'Urla', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jacqueline Urla', 'EmailAddress': 'jurla@anthro.umass.edu', 'NSF_ID': '000331936', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Massachusetts Amherst', 'CityName': 'AMHERST', 'ZipCode': '010039252', 'PhoneNumber': '4135450698', 'StreetAddress': '101 COMMONWEALTH AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'MA02', 'ORG_UEI_NUM': 'VGJHK59NMPK9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MASSACHUSETTS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Massachusetts Amherst', 'CityName': 'AMHERST', 'StateCode': 'MA', 'ZipCode': '010039252', 'StreetAddress': '101 COMMONWEALTH AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'MA02'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~712840
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439846.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 53,000 | 53,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/16/2024
|
08/16/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439847
|
{'FirstName': 'Tesfay', 'LastName': 'Meressi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tesfay Meressi', 'EmailAddress': 'tmeressi@umassd.edu', 'NSF_ID': '000486919', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Massachusetts, Dartmouth', 'CityName': 'NORTH DARTMOUTH', 'ZipCode': '027472356', 'PhoneNumber': '5089998953', 'StreetAddress': '285 OLD WESTPORT RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'MA09', 'ORG_UEI_NUM': 'PMMKPCKNN9R2', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MASSACHUSETTS DARTMOUTH', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Massachusetts, Dartmouth', 'CityName': 'DARTMOUTH', 'StateCode': 'MA', 'ZipCode': '027472356', 'StreetAddress': '285 OLD WESTPORT RD NORTH', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'MA09'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~53000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439847.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 159,000 | 159,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/16/2024
|
08/16/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439848
|
{'FirstName': 'Jasbir', 'LastName': 'Dhaliwal', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jasbir Dhaliwal', 'EmailAddress': 'jdhaliwl@memphis.edu', 'NSF_ID': '000802482', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Memphis', 'CityName': 'MEMPHIS', 'ZipCode': '381520001', 'PhoneNumber': '9016783251', 'StreetAddress': '115 JOHN WILDER TOWER', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Tennessee', 'StateCode': 'TN', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'TN09', 'ORG_UEI_NUM': 'F2VSMAKDH8Z7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MEMPHIS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Memphis', 'CityName': 'MEMPHIS', 'StateCode': 'TN', 'ZipCode': '381520001', 'StreetAddress': '115 JOHN WILDER TOWER', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Tennessee', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'TN09'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~159000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439848.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 600,227 | 600,227 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439850
|
{'FirstName': 'Nicole', 'LastName': 'Piquero', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nicole Piquero', 'EmailAddress': 'nxl491@miami.edu', 'NSF_ID': '0000A05DY', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Miami', 'CityName': 'CORAL GABLES', 'ZipCode': '331462919', 'PhoneNumber': '3052843924', 'StreetAddress': '1320 SOUTH DIXIE HIGHWAY STE 650', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '27', 'CONGRESS_DISTRICT_ORG': 'FL27', 'ORG_UEI_NUM': 'RQMFJGDTQ5V3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MIAMI', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Miami', 'CityName': 'CORAL GABLES', 'StateCode': 'FL', 'ZipCode': '331462919', 'StreetAddress': '1320 SOUTH DIXIE HIGHWAY STE 650', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '27', 'CONGRESS_DISTRICT_PERF': 'FL27'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~600227
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439850.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 105,538 | 105,538 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439851
|
{'FirstName': 'Debra', 'LastName': 'Hope', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Debra A Hope', 'EmailAddress': 'dhope1@unl.edu', 'NSF_ID': '000864072', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Nebraska-Lincoln', 'CityName': 'LINCOLN', 'ZipCode': '685032427', 'PhoneNumber': '4024723171', 'StreetAddress': '2200 VINE ST # 830861', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Nebraska', 'StateCode': 'NE', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NE01', 'ORG_UEI_NUM': 'HTQ6K6NJFHA6', 'ORG_LGL_BUS_NAME': 'BOARD OF REGENTS OF THE UNIVERSITY OF NEBRASKA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Nebraska-Lincoln', 'CityName': 'LINCOLN', 'StateCode': 'NE', 'ZipCode': '685032427', 'StreetAddress': '2200 VINE ST # 830861', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Nebraska', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NE01'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~105538
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439851.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 97,500 | 97,500 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/16/2024
|
08/16/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439852
|
{'FirstName': 'Eduardo', 'LastName': 'Robleto', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eduardo Robleto', 'EmailAddress': 'eduardo.robleto@unlv.edu', 'NSF_ID': '000337719', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Nevada Las Vegas', 'CityName': 'LAS VEGAS', 'ZipCode': '891549900', 'PhoneNumber': '7028951357', 'StreetAddress': '4505 S MARYLAND PKWY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Nevada', 'StateCode': 'NV', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NV01', 'ORG_UEI_NUM': 'DLUTVJJ15U66', 'ORG_LGL_BUS_NAME': 'BOARD OF REGENTS OF NEVADA SYSTEM OF HIGHER EDUCATION', 'ORG_PRNT_UEI_NUM': 'F995DBS4SRN3'}
|
{'Name': 'University of Nevada Las Vegas', 'CityName': 'LAS VEGAS', 'StateCode': 'NV', 'ZipCode': '891549900', 'StreetAddress': '4505 S MARYLAND PKWY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Nevada', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NV01'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~97500
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439852.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 616,950 | 616,950 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439853
|
{'FirstName': 'Maria', 'LastName': 'Lane', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Maria D Lane', 'EmailAddress': 'mdlane@unm.edu', 'NSF_ID': '000265012', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of New Mexico', 'CityName': 'ALBUQUERQUE', 'ZipCode': '87131', 'PhoneNumber': '5052774186', 'StreetAddress': '1700 LOMAS BLVD NE STE 2200', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Mexico', 'StateCode': 'NM', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NM01', 'ORG_UEI_NUM': 'F6XLTRUQJEN4', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NEW MEXICO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of New Mexico', 'CityName': 'ALBUQUERQUE', 'StateCode': 'NM', 'ZipCode': '871063837', 'StreetAddress': '1700 LOMAS BLVD NE STE 2200', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Mexico', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NM01'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~616950
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439853.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 927,909 | 927,909 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439854
|
{'FirstName': 'Elizabeth', 'LastName': 'Mayer-Davis', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Elizabeth Mayer-Davis', 'EmailAddress': 'mayerdav@email.unc.edu', 'NSF_ID': '000894897', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of North Carolina at Chapel Hill', 'CityName': 'CHAPEL HILL', 'ZipCode': '275995023', 'PhoneNumber': '9199663411', 'StreetAddress': '104 AIRPORT DR STE 2200', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'NC04', 'ORG_UEI_NUM': 'D3LHU66KBLD5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL', 'ORG_PRNT_UEI_NUM': 'D3LHU66KBLD5'}
|
{'Name': 'University of North Carolina at Chapel Hill', 'CityName': 'CHAPEL HILL', 'StateCode': 'NC', 'ZipCode': '275995023', 'StreetAddress': 'Address 104 AIRPORT DR STE 2200', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'NC04'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~927909
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439854.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 106,000 | 106,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/02/2024
|
08/06/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439855
|
[{'FirstName': 'Christopher', 'LastName': 'Finelli', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christopher M Finelli', 'EmailAddress': 'finellic@uncw.edu', 'NSF_ID': '000160815', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Stuart', 'LastName': 'Borrett', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stuart R Borrett', 'EmailAddress': 'borretts@uncw.edu', 'NSF_ID': '000371719', 'StartDate': '08/02/2024', 'EndDate': '08/06/2024', 'RoleCode': 'Former Principal Investigator'}]
|
{'Name': 'University of North Carolina at Wilmington', 'CityName': 'WILMINGTON', 'ZipCode': '284033201', 'PhoneNumber': '9109623167', 'StreetAddress': '601 S COLLEGE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'NC07', 'ORG_UEI_NUM': 'L1GPHS96MUE1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NORTH CAROLINA AT WILMINGTON', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of North Carolina at Wilmington', 'CityName': 'WILMINGTON', 'StateCode': 'NC', 'ZipCode': '284033201', 'StreetAddress': '601 S COLLEGE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'NC07'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~106000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439855.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 212,000 | 212,000 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439857
|
{'FirstName': 'Gregory', 'LastName': 'Bell', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gregory Bell', 'EmailAddress': 'gcbell@uncg.edu', 'NSF_ID': '000513716', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of North Carolina Greensboro', 'CityName': 'GREENSBORO', 'ZipCode': '274125068', 'PhoneNumber': '3363345878', 'StreetAddress': '1000 SPRING GARDEN ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'NC06', 'ORG_UEI_NUM': 'C13DF16LC3H4', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NORTH CAROLINA AT GREENSBORO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of North Carolina Greensboro', 'CityName': 'GREENSBORO', 'StateCode': 'NC', 'ZipCode': '274125068', 'StreetAddress': '1000 SPRING GARDEN ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'NC06'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~212000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439857.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 495,144 | 495,144 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439858
|
{'FirstName': 'Randall', 'LastName': 'Hewes', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Randall S Hewes', 'EmailAddress': 'hewes@ou.edu', 'NSF_ID': '000337635', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Oklahoma Norman Campus', 'CityName': 'NORMAN', 'ZipCode': '730193003', 'PhoneNumber': '4053254757', 'StreetAddress': '660 PARRINGTON OVAL RM 301', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oklahoma', 'StateCode': 'OK', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'OK04', 'ORG_UEI_NUM': 'EVTSTTLCEWS5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF OKLAHOMA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Oklahoma Norman Campus', 'CityName': 'NORMAN', 'StateCode': 'OK', 'ZipCode': '730193003', 'StreetAddress': '660 PARRINGTON OVAL RM 301', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oklahoma', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'OK04'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~495144
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439858.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 513,918 | 513,918 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439859
|
{'FirstName': 'Anthony', 'LastName': 'Vamivakas', 'PI_MID_INIT': 'N', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anthony N Vamivakas', 'EmailAddress': 'nick.vamivakas@rochester.edu', 'NSF_ID': '000606173', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Rochester', 'CityName': 'ROCHESTER', 'ZipCode': '146113847', 'PhoneNumber': '5852754031', 'StreetAddress': '910 GENESEE ST', 'StreetAddress2': 'STE 200', 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'NY25', 'ORG_UEI_NUM': 'F27KDXZMF9Y8', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ROCHESTER', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Rochester', 'CityName': 'ROCHESTER', 'StateCode': 'NY', 'ZipCode': '146113847', 'StreetAddress': 'Address 910 GENESEE ST STE 200', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'NY25'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~513918
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439859.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
09/01/2024
|
08/31/2029
| 411,166 | 411,166 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Narcrisha Norman', 'PO_EMAI': 'nnorman@nsf.gov', 'PO_PHON': '7032927965'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/15/2024
|
08/15/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439860
|
{'FirstName': 'Timothy', 'LastName': 'Mousseau', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Timothy A Mousseau', 'EmailAddress': 'mousseau@sc.edu', 'NSF_ID': '000569434', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of South Carolina at Columbia', 'CityName': 'COLUMBIA', 'ZipCode': '292083403', 'PhoneNumber': '8037777093', 'StreetAddress': '1600 HAMPTON ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'South Carolina', 'StateCode': 'SC', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'SC06', 'ORG_UEI_NUM': 'J22LNTMEDP73', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF SOUTH CAROLINA', 'ORG_PRNT_UEI_NUM': 'J22LNTMEDP73'}
|
{'Name': 'University of South Carolina at Columbia', 'CityName': 'COLUMBIA', 'StateCode': 'SC', 'ZipCode': '292083403', 'StreetAddress': '1600 HAMPTON ST COLUMBIA, SC', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'South Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'SC06'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~411166
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439860.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 764,167 | 764,167 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439861
|
{'FirstName': 'Dixie', 'LastName': 'Thompson', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dixie L Thompson', 'EmailAddress': 'dixielee@utk.edu', 'NSF_ID': '000720565', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Tennessee Knoxville', 'CityName': 'KNOXVILLE', 'ZipCode': '379960001', 'PhoneNumber': '8659743466', 'StreetAddress': '201 ANDY HOLT TOWER', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Tennessee', 'StateCode': 'TN', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'TN02', 'ORG_UEI_NUM': 'FN2YCS2YAUW3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TENNESSEE', 'ORG_PRNT_UEI_NUM': 'LXG4F9K8YZK5'}
|
{'Name': 'University of Tennessee Knoxville', 'CityName': 'KNOXVILLE', 'StateCode': 'TN', 'ZipCode': '379960001', 'StreetAddress': '201 ANDY HOLT TOWER', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Tennessee', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'TN02'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~764167
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439861.xml'}
|
Graduate Research Fellowship Program (GRFP)
|
NSF
|
08/15/2024
|
07/31/2029
| 565,280 | 565,280 |
{'Value': 'Fellowship Award'}
|
{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}
|
{'SignBlockName': 'Jong-on Hahm', 'PO_EMAI': 'jhahm@nsf.gov', 'PO_PHON': '7032928013'}
|
The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.076
|
1
|
4900
|
4900
|
2439862
|
{'FirstName': 'Andrew', 'LastName': 'Zinn', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andrew R Zinn', 'EmailAddress': 'Andrew.Zinn@UTSouthwestern.edu', 'NSF_ID': '000706440', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Texas Southwestern Medical Center', 'CityName': 'DALLAS', 'ZipCode': '753907208', 'PhoneNumber': '2146484494', 'StreetAddress': '5323 HARRY HINES BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '30', 'CONGRESS_DISTRICT_ORG': 'TX30', 'ORG_UEI_NUM': 'YZJ6DKPM4W63', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF TEXAS SOUTHWESTERN MEDICAL CENTER', 'ORG_PRNT_UEI_NUM': 'X5NKD2NFF2V3'}
|
{'Name': 'University of Texas Southwestern Medical Center', 'CityName': 'DALLAS', 'StateCode': 'TX', 'ZipCode': '753907208', 'StreetAddress': '5323 HARRY HINES BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '30', 'CONGRESS_DISTRICT_PERF': 'TX30'}
|
{'Code': '717200', 'Text': 'Graduate Research Fellowship'}
|
2024~565280
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439862.xml'}
|
Conference: ASM Conference for Undergraduate Educators
|
NSF
|
08/15/2024
|
07/31/2025
| 49,999 | 49,999 |
{'Value': 'Standard Grant'}
|
{'Code': '08080000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DBI', 'LongName': 'Div Of Biological Infrastructure'}}
|
{'SignBlockName': "Sally O'Connor", 'PO_EMAI': 'soconnor@nsf.gov', 'PO_PHON': '7032924552'}
|
The American Society for Microbiology Conference for Undergraduate Educators (ASMCUE) will be held November 15-17, 2024, in Pittsburgh, Pennsylvania. ASMCUE is an annual 3-day gathering of biology and microbiology educators, representing all types of institutions of higher education. More than 350 biologists, of whom 95% reside in the United States, attend each year to access sessions on teaching, learning and assessment, student advising, student research, mentoring, and professional skills development. An exhibit hall features public and private organizations showcasing faculty resources and tools. ASMCUE has been a signature program for building capacity for evidence-based microbiology teaching and mentoring, generating new ideas for advancing the profession of STEM education, and launching new initiatives for ASM-sponsored teaching resources.<br/><br/>This award to ASM will support first time attendee faculty from community colleges and minority serving institutions to experience ASMCUE and engage with other faculty to share tips and tools on pedagogy and teaching strategies. Programming will include a peer mentoring program featuring organized structured activities for first time participants. In addition, NSF representatives will have a platform to present in a session focused on NSF grant opportunities and provide information on the NSF grant application process and merit review system. Following the NSF scheduled session, a forum will be provided to host small group and one on one consultations during the exhibit hall hours. An evaluation of the ASMCUE experience will be done through a survey. This award is supported by the Division of Biological Infrastructure (DBI) in the Directorate for Biological Sciences (BIO) and the Division for Undergraduate Education (DUE) in the Directorate for STEM Education (EDU).<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/12/2024
|
08/12/2024
|
None
|
Grant
|
47.074, 47.076
|
1
|
4900
|
4900
|
2439865
|
{'FirstName': 'Irene', 'LastName': 'Hulede', 'PI_MID_INIT': 'V', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Irene V Hulede', 'EmailAddress': 'ihulede@asmusa.org', 'NSF_ID': '000937387', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'American Society For Microbiology', 'CityName': 'WASHINGTON', 'ZipCode': '200362904', 'PhoneNumber': '2029429269', 'StreetAddress': '1752 N ST NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'District of Columbia', 'StateCode': 'DC', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DC00', 'ORG_UEI_NUM': 'LJDQSS1E5ST7', 'ORG_LGL_BUS_NAME': 'AMERICAN SOCIETY FOR MICROBIOLOGY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'American Society For Microbiology', 'CityName': 'WASHINGTON', 'StateCode': 'DC', 'ZipCode': '200362904', 'StreetAddress': '1752 N ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'District of Columbia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DC00'}
|
[{'Code': '113900', 'Text': 'RSCH EXPER FOR UNDERGRAD SITES'}, {'Code': '199800', 'Text': 'IUSE'}]
|
2024~49999
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439865.xml'}
|
CNH2-L: Linkages and Interactions Between Urban Food Security and Rural Agricultural Systems
|
NSF
|
02/01/2024
|
02/28/2025
| 1,599,627 | 495,031 |
{'Value': 'Standard Grant'}
|
{'Code': '08010000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DEB', 'LongName': 'Division Of Environmental Biology'}}
|
{'SignBlockName': 'Paco Moore', 'PO_EMAI': 'fbmoore@nsf.gov', 'PO_PHON': '7032925376'}
|
This research investigates the linkages and interactions between urban food security and rural agricultural production. Specifically, the project evaluates the impacts of environmental variability on rural agricultural production and how this affects urban food security, and, in turn, how urban population growth affects the demand for local and regional agricultural production, as measured through food trade and other flows. Future challenges lie ahead in terms of meeting urban food demand due to population growth, the changing nature of food consumption patterns, and the vulnerability of both local and regional food production to environmental variability. Globalization and international flows and trade of food and commodities are key aspects of how urban areas will meet future food demand. But urban areas exhibit different levels of connectivity to international, regional, and local food systems. Given complex patterns of urbanization and their differential engagement with global, regional, and local food supply chains, new research is needed to understand what types of urban places are most vulnerable to impacts of local and regional crop production, and what type of urban agglomerations can mitigate those impacts through food imports from distant areas. This project produces a new and transformative understanding of the challenges of maintaining future urban food security and how local, regional, and global food flows affect urban food security under different socio-environmental conditions. This has implications for national security issues and is of concern for economic development. The project includes educational and stakeholder engagement and disseminates academic and policy relevant materials.<br/><br/>The project uses a novel spatial network approach to model the flow of food within regions and across international borders by analyzing rural food production under recent and projected urban food demand scenarios. This spatial analysis is linked to household survey data collected in urban areas of different sizes and within different geographic contexts to understand how shocks in rural agricultural production affect urban food flows. Household level information is linked to food demand and production information, as well as pricing information. While there has been a considerable amount of research focusing on the drivers and outcomes of rural food insecurity, less work has been done to understand the drivers of urban food insecurity. Additionally, most urban food security research has focused on large metropolitan areas, mostly primate cities, despite the reality that significant numbers of urban residents live in small to moderate sized urban places. This project will make important theoretical advancements in integrated socio-environmental systems research and will make methodological contributions by modelling urban-rural feedbacks and integration and by developing ways of understanding the increasingly important small-to-moderate urban dimension of food security. The research will be conducted in a variety of settings, but the application of the findings is relevant to many urban areas undergoing socio-environmental change, and how this impacts urban food security.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/07/2024
|
08/21/2024
|
None
|
Grant
|
47.074, 47.075
|
1
|
4900
|
4900
|
2439879
|
[{'FirstName': 'Kevin', 'LastName': 'Anchukaitis', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kevin J Anchukaitis', 'EmailAddress': 'kanchukaitis@email.arizona.edu', 'NSF_ID': '000499952', 'StartDate': '08/07/2024', 'EndDate': '08/21/2024', 'RoleCode': 'Former Principal Investigator'}, {'FirstName': 'Lyndon', 'LastName': 'Estes', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lyndon Estes', 'EmailAddress': 'lyndon.estes@gmail.com', 'NSF_ID': '000746051', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'Clark University', 'CityName': 'WORCESTER', 'ZipCode': '016101400', 'PhoneNumber': '5084213835', 'StreetAddress': '950 MAIN ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'MA02', 'ORG_UEI_NUM': 'LD3WUVEUK2N5', 'ORG_LGL_BUS_NAME': 'TRUSTEES OF CLARK UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': 'RI REQUIRED', 'StateName': 'RI REQUIRED', 'CountryFlag': '0', 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
|
{'Code': '169100', 'Text': 'DYN COUPLED NATURAL-HUMAN'}
|
2019~495029
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439879.xml'}
|
EAGER: Establish a New Paradigm in SOFC/SOEC Surface Segregation Modeling
|
NSF
|
08/15/2024
|
07/31/2025
| 96,528 | 96,528 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Robert McCabe', 'PO_EMAI': 'rmccabe@nsf.gov', 'PO_PHON': '7032924826'}
|
This EArly-concept Grant for Exploratory Research (EAGER) project conceives and studies a novel computational approach to predicting the surface composition of solid oxide electrochemical devices under long-term use in energy related chemical applications. Solid oxide fuel cells (SOFCs), in particular, are amongst the most energy-efficient devices available for generating electrical energy. Both SOFC and related solid oxide electrolysis cell (SOEC) technology are positioned to play an important role in the transition to net-zero carbon emissions. However, the devices operate at high temperature, which over time in service can lead to degradation in structural stability and performance. The project will link theoretical and experimental approaches to better understand the degradation mechanisms of solid oxide exchange catalysts, and use the resultant insights to predict more stable, and better performing materials compositions than currently available. <br/><br/>The project will support computational analysis to develop refined predictive models of oxide dopant surface-segregation of strontium (Sr) in ABO3 perovskites under electrical conditions characteristic of Solid Oxide Fuel Cell (SOFC), Solid Oxide Electrolysis Cell (SOEC), and reversible Solid Oxide Cell (rSOC) devices. The study is motivated by the fact that past studies have primarily relied on the size and/or charge mismatch between a dopant ion, and the host ion it is replacing, to capture the driving force for dopant segregation out of bulk perovskite lattice structures. However, such predictions are in direct opposition to recently published experimental observations showing that - while there is significant Sr surface segregation in La0.6Sr0.4Fe0.2Co0.8O3-x (LSCF) and La0.6Sr0.4Fe0.8Co0.2O3-x during 1000 hours of 650-700oC open-circuit aging in air - there is little to no Sr surface segregation in Sm0.5Sr0.5CoO3-x (SSC) exposed to identical testing conditions. Those observations have triggered follow-on collaborative work by the investigators indicating, by both experimental and theoretical (i.e., Surface Gibbs Free Energy (SGFE)) analyses, that this is because LSCF is largely Sr-terminated under SOC operating conditions, whereas the SSC surface remains largely Co-terminated. However, SGFE phase diagrams are needed for various members of the (La,Sr,Sm)(Fe,Co)O3-x solid solution family, under an assortment of likely SOFC/SO polarizations, to refine surface segregation predictions and extend them to relevant SOFC/SOE/rSOCs operating conditions. To that end, the investigators will work hand-in-hand to 1) produce DFT-computed SGFE diagrams on a range of (La,Sm,Sr)(Fe,Co)O3-x compositions as a function of temperature (𝑇), oxygen partial pressure (𝑝𝑂2 𝐺𝑎𝑠), and overpotential (𝜂), and 2) compare the predicted results to experimental characterization of the surface structure and oxygen exchange performance obtained at various 𝑇, 𝑝𝑂2 𝐺𝑎𝑠 and 𝜂 conditions.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/07/2024
|
08/07/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2439898
|
{'FirstName': 'Yue', 'LastName': 'Qi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yue Qi', 'EmailAddress': 'yueqi@brown.edu', 'NSF_ID': '000081918', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Brown University', 'CityName': 'PROVIDENCE', 'ZipCode': '029129100', 'PhoneNumber': '4018632777', 'StreetAddress': '1 PROSPECT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Rhode Island', 'StateCode': 'RI', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'RI01', 'ORG_UEI_NUM': 'E3FDXZ6TBHW3', 'ORG_LGL_BUS_NAME': 'BROWN UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'E3FDXZ6TBHW3'}
|
{'Name': 'Brown University', 'CityName': 'PROVIDENCE', 'StateCode': 'RI', 'ZipCode': '029129100', 'StreetAddress': '1 PROSPECT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Rhode Island', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'RI01'}
|
{'Code': '140100', 'Text': 'Catalysis'}
|
2024~96528
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439898.xml'}
|
EAGER: Active Metamaterials for Computing Applications
|
NSF
|
09/01/2024
|
08/31/2026
| 240,000 | 240,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Margaret Kim', 'PO_EMAI': 'sekim@nsf.gov', 'PO_PHON': '7032922967'}
|
Nontechnical Description:<br/>Optical metamaterials are a class of materials that leverage features smaller than the wavelength of light to engineer their optical transmission characteristics. Optical metamaterials have already enabled transformative applications, including flat lenses, optical cloaking, and super-resolution imaging. Due to these broad successes, researchers are now developing active optical metamaterials: metamaterials whose optical transmission characteristics can be changed on the fly, for example, at high speeds (gigahertz) enabled by electrical circuits used to control them. In this project, we aim to leverage a new class of active metamaterials to improve the energy efficiency of large-scale computing applications running in data centers, such as training large language models (LLMs) for artificial intelligence (AI),and performing scientific computing workloads. Specifically, we will leverage active metamaterials to improve the energy efficiency of optical data communication in datacenters, by using electrical control signals for high-speed reconfigurable communication between large networks of computing and memory systems. For many of today’s data centers, the overheads of data communication limit the overall power and performance of computation, often referred to as the “communication wall” or “memory wall”. Using active metamaterials to improve energy efficiency of communication, will directly translate into energy efficiency benefits for humanity’s largest computing applications. <br/><br/>Technical Description:<br/>We propose a disruptive technology for high-performance optical switches based on optical active metamaterials – optical metamaterials whose transmission characteristics can be electrically modulated – for improving the energy efficiency of data communication in large-scale data centers. We are targeting communication in data centers, since overall computing performance is often limited by data communication overheads within the large networks of sub-systems that comprise today’s data centers, including racks of general-purpose processors, application-specific hardware accelerators, and memories. Thus, improving the energy efficiency of communication directly improves the energy efficiency of computing.<br/>In this project, we will explore the benefits of active metamaterials to enable a new class of energy-efficient Active Metamaterial Optical Switches (AMOS), targeting high-performance communication and computation in data centers. We will explore three areas of focus: (1) Design and simulation of AMOS devices, considering three potential device structures (details in the full proposal), which we will compare based on their relative power, performance, and area. (2) Experimental fabrication of AMOS devices in our cleanroom (Harvard’s Center for Nanoscale Systems),and experimental measurements to calibrate our device models. (3) System-level projections to quantify the benefits of our AMOS devices for overall power consumption and execution time of computing applications in data centers. Importantly, our analysis will account for interactions between AMOS devices and the power/performance overheads of electrical circuits required to modulate them. This is essential for realistic performance projections of real-world applications. If successful, AMOS devices will enable strictly better trade-offs in switching time, latency, bandwidth, power consumption, and physical size of optical network switches. The resulting energy efficiency benefits of communication will translate directly into energy efficiency benefits of computation for large-scale data centers employing AMOS devices.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/12/2024
|
08/12/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2439922
|
{'FirstName': 'Gage', 'LastName': 'Hills', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gage Hills', 'EmailAddress': 'ghills@seas.harvard.edu', 'NSF_ID': '000841281', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Harvard University', 'CityName': 'CAMBRIDGE', 'ZipCode': '021385366', 'PhoneNumber': '6174955501', 'StreetAddress': '1033 MASSACHUSETTS AVE STE 3', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MA05', 'ORG_UEI_NUM': 'LN53LCFJFL45', 'ORG_LGL_BUS_NAME': 'PRESIDENT AND FELLOWS OF HARVARD COLLEGE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Harvard University', 'CityName': 'CAMBRIDGE', 'StateCode': 'MA', 'ZipCode': '021385366', 'StreetAddress': '1033 MASSACHUSETTS AVE STE 3', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MA05'}
|
{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}
|
2024~240000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439922.xml'}
|
EAGER: Quantum Emitters in Silicon and Devices for Scalable Quantum Networks
|
NSF
|
05/01/2025
|
04/30/2027
| 275,000 | 275,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Dominique Dagenais', 'PO_EMAI': 'ddagenai@nsf.gov', 'PO_PHON': '7032922980'}
|
Quantum light sources will play a fundamental role in the future of technologies including quantum communications, sensing, and computing. Although many types of quantum emitters have been investigated, they all face long standing challenges making it fundamentally difficult to scale quantum systems to larger systems. This work will focus on silicon, an intrinsically scalable material platform and investigate a particular emitter with strong potential for spin-photon interface in the telecommunication band. The multidisciplinary project will contribute to national quantum initiatives and will be coupled with numerous educational objectives including (1) the full participation of underrepresented minorities via presentations at Historically Black Colleges and Universities (HBCUs), and (2) the integration of K-12 students and undergraduate students in the research.<br/><br/>Technical description: Solid state quantum emitters require fabrication at the atomic and molecular scales and have suffered from challenges such as reproducibility when fabricated in a host material. Additionally, many quantum sources do not emit in the telecom band and thus require nonlinear processes to make the single photon useful, affecting system energy efficiency. This work will help understand the properties of newly discovered quantum light emitters in silicon. Such emitters can power future quantum networks and computers. The prospect of quantum optics in silicon is an exciting avenue because it has the potential to address the scaling and integration challenges. The exploratory proposal will investigate (1) the manufacturing of the new defect in silicon, (2) the characterization of color centers in silicon, and (3) the spin properties of the defect in silicon.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/01/2024
|
08/01/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2439937
|
{'FirstName': 'Boubacar', 'LastName': 'Kante', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Boubacar Kante', 'EmailAddress': 'bkante@berkeley.edu', 'NSF_ID': '000659479', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'ZipCode': '947101749', 'PhoneNumber': '5106433891', 'StreetAddress': '1608 4TH ST STE 201', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'GS3YEVSS12N6', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'StateCode': 'CA', 'ZipCode': '947101749', 'StreetAddress': '1608 4TH ST STE 201', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}
|
{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}
|
2024~275000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2439937.xml'}
|
Conference: US-RSE 2024
|
NSF
|
08/15/2024
|
07/31/2025
| 50,000 | 50,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}
|
{'SignBlockName': 'Varun Chandola', 'PO_EMAI': 'vchandol@nsf.gov', 'PO_PHON': '7032922656'}
|
Over the past decade, Research Software Engineers (RSEs) have been increasingly recognized by academia and national labs for their crucial role enabling and accelerating scientific and engineering discovery. The acknowledgement is evident in many projects and initiatives such as the founding of eight Research Software Engineer Associations worldwide, the NSF Cybertraining INTERSECT for RSEs, and the initiative Better Scientific Software driven mostly by national labs. Since 2021 NSF has explicitly included the term "RSE" as a Cyberinfrastructure professional in solicitations such as the NSF Cyberinfrastructure for Sustained Scientific Innovation (CSSI) that has been open for submissions annually since 2018. The US-RSE Association is the leading professional community of research software engineering practitioners in the United States. The organization and its ~2500 members are dedicated to creating research software that is fit for purpose, sustainable over the long-term and reliably developed and supported. The members come from diverse backgrounds but share a common goal: to support and promote the role of research software and research software engineers in driving innovation and solving complex problems. The US-RSE Association has members from all over the country, representing a diverse range of research institutions, including academic institutions, national labs, and industry. The members work in various scientific fields, including but not limited to physics, life science, chemistry, geosciences, engineering, and social sciences. The first-ever US-RSE conference in 2023 hosted 250 attendees and over a hundred virtual attendees for online tutorials. Attendees included students, researchers, software developers, IT staff, data professionals, and educators. This travel grant allows more students and early-career researchers to be involved in US-RSE 2024.<br/><br/>US-RSE 2024 is the major event for the RSE community in the US to build the community, to discuss challenges and solutions in research software engineering. Topics of interest for the 2024 conference include past or present research software engineering research and practice, research software engineering techniques, frameworks, libraries, research data management, reproducibility, and software sustainability. The meeting also explores diversity, equity, and inclusion issues in research software engineering, workforce development, and building a robust and sustainable RSE profession. The knowledge transfer can be transformative between different research domains and technical content. The US-RSE conference sets the stage for learning, engaging and empowering the different stakeholders in the community and to foster innovation and collaboration. Research software is crucial for many research areas that need computational tools, addressing large challenges such as genomics, pandemics, climate change, global sustainability on food, water and land use driven by growing population and rising per capita incomes. By attending the US-RSE Conference, students and early-career researchers will gain exposure to the latest advancements in research software engineering. This experience will provide critical skills and knowledge that are essential for growth and success in the field. The opportunity to engage with cutting-edge discussions will enhance technical competencies and inspire innovative approaches in research endeavors. Providing travel grants for students and early-career researchers will include a diverse audience and support underrepresented minorities.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2440011
|
{'FirstName': 'Sandra', 'LastName': 'Gesing', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sandra Gesing', 'EmailAddress': 'sgesing@ucsd.edu', 'NSF_ID': '000669642', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'ZipCode': '920930021', 'PhoneNumber': '8585344896', 'StreetAddress': '9500 GILMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_ORG': 'CA50', 'ORG_UEI_NUM': 'UYTTZT6G9DT1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, SAN DIEGO', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'StateCode': 'CA', 'ZipCode': '920930021', 'StreetAddress': '9500 GILMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_PERF': 'CA50'}
|
{'Code': '736100', 'Text': 'EDUCATION AND WORKFORCE'}
|
2024~50000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2440011.xml'}
|
CAREER: Guided Exploration of Multiphysics Design Space for Electric Machines Using Tensorial Analysis (GEOMETRY)
|
NSF
|
08/01/2024
|
12/31/2028
| 549,936 | 413,931 |
{'Value': 'Continuing Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Mahesh Krishnamurthy', 'PO_EMAI': 'mkrishna@nsf.gov', 'PO_PHON': '7032928359'}
|
The year 2023 has witnessed the hottest days on Earth since 1940, highlighting the urgency of the fight against climate change and excessive carbon emissions. In this mission, motors and generators, or collectively electric machines (EMs), play a pivotal role. Through EMs, over 90% of global electricity is generated, 45% of which is turned into mechanical work. EMs are at the heart of electric vehicles (EVs), wind energy generation, and various industrial processes, propelling these essential applications forward. To push EM performance boundaries, it is crucial to explore the multiphysics design space, which encompasses the interplay of various physical disciplines, such as electrodynamics, heat transfer, and structural mechanics. The multiphysics design space is confined by EM topologies, i.e., arrangements of constituent parts in EMs including steel, copper, magnets, etc. A natural question to ask is: what are the best arrangements of these constituent parts? The proposed research is poised to systematically answer this fundamental question and accelerate the exploration of high-performance and highly sustainable EMs. Parallel to the research, the PI’s education goal is to systematically foster diverse multiphysics designers, including those who are underrepresented. The PI’s education activities will include constructing a website-based learning platform named TENSOR to create an inclusive multiphysics learning hub, implementing a duality and analogy-based multiphysics education technique for K-12, undergraduate, and graduate students, and offering an open-access new EM design course to the frontier EM workforce.<br/>In the existing design paradigm, new EM topologies are often conceived by designers and the conception relies on their intuition, resulting in sporadically revealing new design space and corresponding performance space. To overcome the limitations of this intuition-based design paradigm, the overarching goal of this CAREER project is to pioneer a new design paradigm — multiphysics synthesis which realizes guided exploration of multiphysics design space for EMs using tensorial analysis. To achieve this goal, three research thrusts are planned. First, primitive EMs, governed by electrodynamics and expressed in hyperdimensional space, will be used as starting points to derive new topologies. Second, the hyperdimensional models of EMs will be embodied in the 3D space for performance evaluation and optimization. Third, the methodologies in the first two thrusts will be generalized to incorporate physics beyond electrodynamics and fulfill multiphysics synthesis. In all three thrusts, tensorial analysis originated from mathematics (geometry) and theoretical physics (relativity theory) will be applied.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/08/2024
|
08/08/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2440056
|
{'FirstName': 'Baoyun', 'LastName': 'Ge', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Baoyun Ge', 'EmailAddress': 'baoyun.ge@ece.gatech.edu', 'NSF_ID': '000876809', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'ZipCode': '303186395', 'PhoneNumber': '4048944819', 'StreetAddress': '926 DALNEY ST NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'EMW9FC8J3HN4', 'ORG_LGL_BUS_NAME': 'GEORGIA TECH RESEARCH CORP', 'ORG_PRNT_UEI_NUM': 'EMW9FC8J3HN4'}
|
{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'StateCode': 'GA', 'ZipCode': '303186395', 'StreetAddress': '926 DALNEY ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'GA05'}
|
{'Code': '760700', 'Text': 'EPCN-Energy-Power-Ctrl-Netwrks'}
|
2024~413931
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2440056.xml'}
|
HCC: Travel: Student Travel Grant for the 2024 ACM International Conference in Ubiquitous and Mobile Computing (Ubicomp)
|
NSF
|
09/01/2024
|
08/31/2025
| 22,000 | 22,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
|
{'SignBlockName': 'Dan Cosley', 'PO_EMAI': 'dcosley@nsf.gov', 'PO_PHON': '7032928832'}
|
This grant supports United States (U.S.) student attendance at the 2024 version of the ACM International Conference in Ubiquitous and Mobile Computing (Ubicomp) and the International Symposium on Wearable Computers (ISWC), which will take place together in Melbourne, Australia. Ubicomp and ISWC are leading events in ubiquitous, mobile, wearable, and interactive computing that foster the exchange of cutting-edge research and innovations among global researchers and practitioners. The conference serves as a platform for advancing knowledge and technological applications in this field, as well as a place to build the research community. Having a strong representation of U.S. student researchers at the conference is crucial to both develop the community and to uphold U.S. competitiveness in this important field. <br/><br/>The grant funds will be used to facilitate up to 16 U.S.-based students attending the doctoral colloquium associated with the conferences. Students will be selected primarily based on the potential of their work's contributions to the field and to society more generally. The selection committee will also give some weight to selecting a set of attendees from a diverse set of institutions and backgrounds, as well as to promising first-time attendees who do not yet have papers at the conference. Attending students will benefit from receiving experienced mentors' feedback on their work as well as the chance to connect to more senior researchers in the field.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2440066
|
{'FirstName': 'Afsaneh', 'LastName': 'Doryab', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Afsaneh Doryab', 'EmailAddress': 'ad4ks@virginia.edu', 'NSF_ID': '000704586', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Virginia Main Campus', 'CityName': 'CHARLOTTESVILLE', 'ZipCode': '229034833', 'PhoneNumber': '4349244270', 'StreetAddress': '1001 EMMET ST N', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'VA05', 'ORG_UEI_NUM': 'JJG6HU8PA4S5', 'ORG_LGL_BUS_NAME': 'RECTOR & VISITORS OF THE UNIVERSITY OF VIRGINIA', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Virginia Main Campus', 'CityName': 'CHARLOTTESVILLE', 'StateCode': 'VA', 'ZipCode': '229034833', 'StreetAddress': '1001 EMMET ST N', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'VA05'}
|
{'Code': '736700', 'Text': 'HCC-Human-Centered Computing'}
|
2024~22000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2440066.xml'}
|
NSF-SNSF: THz Frequency combs with Vertical-External-Cavity Surface-Emitting-Lasers
|
NSF
|
10/01/2024
|
09/30/2027
| 400,000 | 400,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Dominique Dagenais', 'PO_EMAI': 'ddagenai@nsf.gov', 'PO_PHON': '7032922980'}
|
This research addresses the challenge of making terahertz semiconductor laser sources that emit electromagnetic waves with frequencies between 2 and 5 THz (i.e. wavelengths between 60 and 150 microns). More specifically, the goal is to develop new types of high-performance terahertz frequency combs – a type of laser source which emits many colors of light simultaneously, where each “color” has a frequency precisely spaced by a fixed amount from the other frequencies. This is an international collaboration between the UCLA group, which has expertise in a unique type of external-cavity terahertz quantum-cascade (QC) laser, and a Swiss group at ETH Zürich, which has expertise in terahertz frequency comb physics and measurement. If successful, this research would result in a new terahertz source for applications in the fields of astrophysics, atmospheric science, biological and medical sciences, security screening, illicit material detection, combustion science, antiquities, waste-sorting, next-generation wireless communications, and non-destructive evaluation. The broader impacts of the project include training graduate and undergraduate students (including international scientific exchange and visits between the two partners), as well as support recruitment and retention of underrepresented minorities to engineering through participation in a targeted research project course.<br/><br/>The objective of this research is to demonstrate terahertz quantum-cascade (QC) metasurface laser frequency combs (FC), characterize these combs in the frequency and time-domain using novel coherent photonic techniques, and to explore the physics of comb states. This will include frequency-modulated quantum-walk combs as well as amplitude-modulated combs producing ultrafast mode-locked pulses. In the past several years, the UCLA group has pioneered a novel configuration for terahertz QC-lasers in the vertical-external-cavity surface-emitting-laser architecture (VECSEL). The ETH Zurich group brings expertise in the development, physics, and coherent characterization of waveguide-based THz QC-laser frequency combs. The complementary expertise of both groups will be leveraged in the collaborative development of novel metasurfaces, microfabrication process, and dispersion compensation elements, as well as coherent characterization of the resulting combs for the first time, and exploration of novel frequency comb physics. The intellectual merit lies in the unique region of parameter space made accessible by the QC-VECSEL for the study of frequency comb states. Specifically, (a) QC-laser gain material generally has a fast picosecond gain recovery time (compared to the cavity round-trip time), (b) the amplifying metasurface does not exhibit the spatial hole burning ordinarily found in a Fabry-Pérot cavity, (c) and the external cavity allows adjustment of the cavity round trip time over a large range – both shorter and longer than the gain recovery time. Collectively, these features will allow investigation of both frequency modulated and amplitude modulated comb states, including novel comb states such as the quantum-walk comb. Practically, the QC-VECSEL exhibits many desirable features for applications, including large scalable powers, broad gain bandwidths, excellent near-diffraction limited beam patterns, the ability to readily modulate the cavity length (and thus comb tooth spacing) for tuning and stabilization, and the ability to incorporate additional cavity elements for dispersion compensation. <br/><br/>This collaborative U.S.-Swiss project is supported by the U.S. National Science Foundation (NSF) and the Swiss National Science Foundation (SNSF), where NSF funds the U.S. investigator and SNSF funds the partners in Switzerland.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/12/2024
|
08/12/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2440163
|
{'FirstName': 'Benjamin', 'LastName': 'Williams', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Benjamin S Williams', 'EmailAddress': 'bswilliams@ucla.edu', 'NSF_ID': '000513615', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-Los Angeles', 'CityName': 'LOS ANGELES', 'ZipCode': '900244200', 'PhoneNumber': '3107940102', 'StreetAddress': '10889 WILSHIRE BLVD STE 700', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '36', 'CONGRESS_DISTRICT_ORG': 'CA36', 'ORG_UEI_NUM': 'RN64EPNH8JC6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, LOS ANGELES', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Los Angeles', 'CityName': 'LOS ANGELES', 'StateCode': 'CA', 'ZipCode': '900244200', 'StreetAddress': '420 Westwood Plaza', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '36', 'CONGRESS_DISTRICT_PERF': 'CA36'}
|
{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}
|
2024~400000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2440163.xml'}
|
Conference: Research Needs in Engineering of Electrochemical Conversions
|
NSF
|
09/15/2024
|
08/31/2025
| 94,479 | 94,479 |
{'Value': 'Standard Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Carole Read', 'PO_EMAI': 'cread@nsf.gov', 'PO_PHON': '7032922418'}
|
This award supports the organization of a workshop on Research Needs in Engineering of Electrochemical Conversions. The workshop will advance an important area for providing a path to high-efficiency, low-emission alternatives to fossil-fuel-driven thermochemical processes. Such a path is likely necessary to achieve economy-scale decarbonization. The workshop will be held in the Knoxville, Tennessee in the fall of 2024 and it is expected that there will be 50 in-person participants, and the workshop sessions will be live broadcast to virtual observers. The workshop will have sessions that focus on early career investigators to inform the research community of the needs and emerging trends in electrochemical systems research. The workshop will take place over two-and-a-half days and will include interactive sessions and a poster session to explore and define critical fundamental engineering science research needs in electrochemical systems, components, and materials for applications in energy and chemical processing. <br/><br/>The workshop will focus on the reaction and process engineering and science associated with electrochemical conversions for the chemical and energy industries. Engineering aspects of electrolysis of chemicals and water is the target scope, including: systems considerations: from electrochemical cells to grid-integrated electrochemical plants; processes in electrolysis and electrosynthesis; generic ‘counterelectrodes’ for use in electrosynthesis, such as oxygen evolving electrodes; materials for conversions, including membranes and porous electrode structures; advanced catalysis for conversions; and Machine Learning (ML), and Artificial Intelligence (AI) methods to accelerate development. The planned outcome from this workshop will be a publicly available white paper on research needs. The interdisciplinary workshop will synthesize the inputs from experts in industry, academia, and the national laboratories on critical fundamental research needs that support electrochemical conversion systems and components.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2440194
|
{'FirstName': 'Thomas', 'LastName': 'Zawodzinski', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thomas Zawodzinski', 'EmailAddress': 'tzawodzi@utk.edu', 'NSF_ID': '000158193', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Tennessee Knoxville', 'CityName': 'KNOXVILLE', 'ZipCode': '379960001', 'PhoneNumber': '8659743466', 'StreetAddress': '201 ANDY HOLT TOWER', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Tennessee', 'StateCode': 'TN', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'TN02', 'ORG_UEI_NUM': 'FN2YCS2YAUW3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TENNESSEE', 'ORG_PRNT_UEI_NUM': 'LXG4F9K8YZK5'}
|
{'Name': 'University of Tennessee Knoxville', 'CityName': 'KNOXVILLE', 'StateCode': 'TN', 'ZipCode': '379960001', 'StreetAddress': '201 ANDY HOLT TOWER', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Tennessee', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'TN02'}
|
{'Code': '764400', 'Text': 'EchemS-Electrochemical Systems'}
|
2024~94479
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2440194.xml'}
|
CAREER: Investigating and Combating Micro Signal Attacks in Video Conferencing
|
NSF
|
06/01/2024
|
05/31/2029
| 619,920 | 251,830 |
{'Value': 'Continuing Grant'}
|
{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}
|
{'SignBlockName': 'Dan Cosley', 'PO_EMAI': 'dcosley@nsf.gov', 'PO_PHON': '7032928832'}
|
Video conferencing applications have been broadly used to connect geographically distant people for work, school, and social interactions. Because they use audio and video, and these can show information about a participant's behavior and environment, people choose to turn off microphones or cameras when they have related privacy concerns. However, microphones and cameras may leak other kinds of information beyond the semantics of what is seen and heard, raising privacy risks people are unaware of. This project's goal is to examine those risks, looking at the many sensitive "micro signals" that are sent over the network through the legitimate visual and acoustic channels of video conferencing. These signals are too tiny for humans to recognize, but detectable by machines, and through careful signal processing they might inadvertently reveal information about people's location, off-camera behavior, interaction with their computer, and other things people might want to keep private. Through better understanding the risks and developing methods to mitigate them, this project will advance understanding of side channel attacks and increase online meeting privacy. The project also contributes to cyber security education through curriculum development, demo platform implementation, graduate/undergraduate student training, K-12 involvement, public outreach, and underrepresented student engagement in research.<br/><br/>This project advances the knowledge of acoustic sensing and visual sensing and brings the security protection of video conferencing down to the micro signal level. It exploits the two-way audio channel of video conferencing to send malicious acoustic signals remotely, which sense the user's current physical surroundings and return to the attacker with location-specific echo signals. Deep learning algorithms are developed to circumvent the echo cancellation mechanisms enforced by audio streaming systems, maximizing the retrieval of sensitive echoes for attackers. The project further uncovers the user's on-screen inputs during video calls, which are out of the webcam's view and believed to be safe, including online voting choices, touchscreen device inputs, and physical keyboard typing. The user's eye motions, keystroke-induced camera vibrations, and the monitor's screen lights are exploited for privacy inference. To prevent privacy leakage from micro signals, this project develops both targeted defense approaches, which address each attack separately, and general micro-signal removal techniques based on compression and decompression, which can handle different micro-signal attacks and their variants.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/28/2024
|
08/28/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2440238
|
{'FirstName': 'Chen', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Chen Wang', 'EmailAddress': 'chenwang1@lsu.edu', 'NSF_ID': '000817720', 'StartDate': '08/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Southern Methodist University', 'CityName': 'DALLAS', 'ZipCode': '752051902', 'PhoneNumber': '2147684708', 'StreetAddress': '6425 BOAZ ST RM 130', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_ORG': 'TX24', 'ORG_UEI_NUM': 'D33QGS3Q3DJ3', 'ORG_LGL_BUS_NAME': 'SOUTHERN METHODIST UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'S88YPE3BLV66'}
|
{'Name': 'Southern Methodist University', 'CityName': 'DALLAS', 'StateCode': 'TX', 'ZipCode': '752051902', 'StreetAddress': '6425 BOAZ ST RM 130', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_PERF': 'TX24'}
|
{'Code': '806000', 'Text': 'Secure &Trustworthy Cyberspace'}
|
2024~251830
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2440238.xml'}
|
Planning: Sonification Network for the Geosciences
|
NSF
|
09/01/2024
|
08/31/2026
| 199,991 | 199,991 |
{'Value': 'Standard Grant'}
|
{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}
|
{'SignBlockName': 'Elizabeth Rom', 'PO_EMAI': 'elrom@nsf.gov', 'PO_PHON': '7032927709'}
|
The practice of representing data as sound, sonification, has been increasing exponentially since the mid 2010s. Although a large portion of these projects focus on astronomical data, sonification in the context of geosciences has the potential to enhance our understanding of complex datasets such as seismic signals, weather patterns, and ocean currents. Whether the motivation for the project is research, outreach, accessibility, education, or art, each must solve a similar set of problems related to how the sonification will be produced and accessed. In addition to researchers fluent in the data to be sonified, addressing these challenges requires input from experts in areas such as neural acoustics, psychology, music, design, and evaluation. Additionally, if the promise of sonification to increase accessibility for blind and low- vision (BLV) persons is to be realized, professionals representing this community need to be part of the design process, not just the recipients of the products.<br/><br/>The Sonification Network for the Geosciences (Geo SonNet) planning project seeks to develop a plan to accelerate the development of high quality, perceivable, interpretable, and accessible data sonifications in the geosciences, including earth, atmosphere, oceans and cryosphere. The planning process will focus on identifying concrete actions that will 1) lead to the creation of stable and interdisciplinary networks of sonification researchers, domain experts, and BLV professionals; (2) provide a foundation of reference literature, web resources, and knowledge-sharing platforms in which standards for sonification can be developed and innovations can occur; and (3) expand the knowledge of data sonification techniques and development practices among geoscience researchers from which future proposals can be launched.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/21/2024
|
08/21/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2440252
|
[{'FirstName': 'Amy', 'LastName': 'Bower', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Amy S Bower', 'EmailAddress': 'abower@whoi.edu', 'NSF_ID': '000094250', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Kathryn', 'LastName': 'Meredith', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kathryn K Meredith', 'EmailAddress': 'kate@glaseducation.org', 'NSF_ID': '000794470', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'Woods Hole Oceanographic Institution', 'CityName': 'WOODS HOLE', 'ZipCode': '025431535', 'PhoneNumber': '5082893542', 'StreetAddress': '266 WOODS HOLE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'MA09', 'ORG_UEI_NUM': 'GFKFBWG2TV98', 'ORG_LGL_BUS_NAME': 'WOODS HOLE OCEANOGRAPHIC INSTITUTION', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Woods Hole Oceanographic Institution', 'CityName': 'WOODS HOLE', 'StateCode': 'MA', 'ZipCode': '025431535', 'StreetAddress': '266 WOODS HOLE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'MA09'}
|
{'Code': '769900', 'Text': 'Integrat & Collab Ed & Rsearch'}
|
2024~199991
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2440252.xml'}
|
EAGER: Electro-Mechanical Energy Conversion System Reliability through Self-Characterization and Self-Healing Approaches
|
NSF
|
08/15/2024
|
07/31/2026
| 249,784 | 249,784 |
{'Value': 'Standard Grant'}
|
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
|
{'SignBlockName': 'Mahesh Krishnamurthy', 'PO_EMAI': 'mkrishna@nsf.gov', 'PO_PHON': '7032928359'}
|
Electro-mechanical energy conversion systems are an essential component of our day-to-day life, ranging from electrified transportation, to manufacturing systems and beyond. These energy conversion systems consist of an array of critical sub-systems of varying degrees of complexity that operate seamlessly and efficiently. Efficient and reliable operation of the system as a whole is governed by the efficient, optimal, and reliable operation of each subsystem. Reduced performance, partial failure, or complete failure of a single subsystem impacts the overall energy conversion process and is deemed costly, wasteful, and possibly harmful. Thus, research on diagnosing inefficiencies, failure mode detection, and fault mitigation in electromechanical energy conversion systems has existed for many decades. However, limitations in the existing fault diagnosis framework necessitate novel and robust approaches. The exploratory research aims to investigate self-optimizing extremum-seeking control (SO-ESC) approaches, which enable the system to self-heal and self-characterize without disrupting the overall energy conversion process. Discoveries made from this work will establish a new paradigm of controllers and novel approaches that allow systems to be highly reliable, aligning with NSF's mission to promote the progress of science and advance the capability of the nation to meet current and future challenges. <br/>The project intends to investigate fundamental approaches that can lead to transformative technology allowing machine-drive systems to self-heal under fault conditions and self-characterize for optimized performance. This will be achieved through a self-optimizing extremum-seeking framework capable of operating under static or dynamic states, in which the underlying sub-systems are monitored and optimized while the energy conversion system is in use. Once implemented, the energy conversion system will be able to 1) optimize performance without human intervention, 2) facilitate online fault mitigation without user/human intervention and 3) specifically localize sub-systems that require attention. The aforementioned outcomes will be achieved with extremum-seeking controls that utilize a minute perturbation to direct the non-linear system to optimal performance. Non-linear properties of fault modes and inefficiencies along with the perturbation used for extremum-seeking, will assist in achieving optimal performance and self-optimization of the extremum-seeking controller in real-time. The ability to self-optimize the extremum-seeking approach adds an additional layer of benefit, enabling the energy conversion systems to maintain optimal performance despite a range of variables changing, which influence system performance.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/12/2024
|
08/12/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2440506
|
{'FirstName': 'Sandun', 'LastName': 'Kuruppu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sandun Kuruppu', 'EmailAddress': 'sandun.kuruppu@wmich.edu', 'NSF_ID': '000819442', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Western Michigan University', 'CityName': 'KALAMAZOO', 'ZipCode': '490085200', 'PhoneNumber': '2693878298', 'StreetAddress': '1903 W MICHIGAN AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MI04', 'ORG_UEI_NUM': 'J7WULLYGFRH1', 'ORG_LGL_BUS_NAME': 'WESTERN MICHIGAN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Western Michigan University', 'CityName': 'KALAMAZOO', 'StateCode': 'MI', 'ZipCode': '490085200', 'StreetAddress': '1903 W MICHIGAN AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MI04'}
|
{'Code': '760700', 'Text': 'EPCN-Energy-Power-Ctrl-Netwrks'}
|
2024~249784
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2440506.xml'}
|
Exploring Long Term Adaptation to Environmental Change
|
NSF
|
01/15/2024
|
06/30/2025
| 244,640 | 86,017 |
{'Value': 'Standard Grant'}
|
{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}
|
{'SignBlockName': 'John Yellen', 'PO_EMAI': 'jyellen@nsf.gov', 'PO_PHON': '7032928759'}
|
Researchers will undertake both underwater and terrestrial research to understand how foraging peoples in the Americas made decisions that enabled them to adapt to the rapid environmental changes that occurred over multiple millenia. During this time, dozens of animal species had recently gone extinct or were dying out or migrating to new lands, plant communities completely transformed, lakes were forming, rivers were flooding, and sea levels rose at least 40 meters. Nevertheless, archaeological data show that people not only adjusted to these transformations, but seem to have thrived, as there are ever-increasing numbers of sites and artifacts appearing throughout this span. Although these groups were entirely reliant upon hunting, gathering, and managing resources available in the world around them, they seem to have met the challenge of extremely rapid and dramatic environmental changes with aplomb. Researchers have long wished to understand how human social, economic, and environmental systems are or are not resilient, and archaeology is particularly well placed to provide relevant insight because it can trace human systems over centuries and millennia. Nuanced understanding of how these forager societies managed to adjust to near-constant change over nearly 5,000 years of rapid environmental fluctuations can provide insight into ways to make human systems more resilient. However, nearly all the known sites contain only lithic artifacts, often in semi-disturbed contexts, severely curtailing what can be learned about social resilience. <br/><br/>Some submerged Florida sites however are an exception. Hundreds of osseous and lithic tools have been recovered from the river, and some mid-channel sinkholes have extensive archaeological remains within intact, dateable deposits. The research team will conduct fieldwork at three sites: two adjacent submerged sinkholes and one interior terrestrial site. The two submerged sites have dateable organics and intact sediment sequences. The terrestrial site will likely not have good organic preservation compared to the sinks, but it will provide data about an area where people were not maximizing access to freshwater. Exploring human relationships with the dynamic land and waterscape entails three research and one pedagogical component: 1) creating a diachronic model of resource availability through time; 2) generating predictions for site distributions by modeling potential resource maximization strategies; and 3) assessing the archaeological record of the basin in light of these frameworks. Data from prior excavations will be combined with the new excavation data to test the utility of central place foraging models . Macro-level (geospatial modeling and paleoenvironmental reconstruction) and micro-level (intrasite analysis of features, lithic artifacts, and preserved organics) will be combined to discuss human use during the terminal Pleistocene and early Holocene. Equally important, this project will train some of the next generation of geoarchaeologists, teaching them how to investigate landscapes in their totality and see the waterline as an opportunity, rather than a boundary, giving them the tools to understand and manage submerging and submerged cultural resources.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/08/2024
|
08/08/2024
|
None
|
Grant
|
47.075
|
1
|
4900
|
4900
|
2440541
|
{'FirstName': 'JESSI', 'LastName': 'HALLIGAN', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'JESSI J HALLIGAN', 'EmailAddress': 'jhalligan@fsu.edu', 'NSF_ID': '000561584', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Texas A&M University', 'CityName': 'COLLEGE STATION', 'ZipCode': '778454375', 'PhoneNumber': '9798626777', 'StreetAddress': '400 HARVEY MITCHELL PKY S STE 30', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'TX10', 'ORG_UEI_NUM': 'JF6XLNB4CDJ5', 'ORG_LGL_BUS_NAME': 'TEXAS A & M UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Texas A&M University', 'CityName': 'COLLEGE STATION', 'StateCode': 'TX', 'ZipCode': '778430001', 'StreetAddress': '340 Spence St', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'TX10'}
|
{'Code': '139100', 'Text': 'Archaeology'}
|
2022~86017
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2440541.xml'}
|
Travel: NSF Student Travel Support for the 2024 IEEE International Conference on Data Mining (IEEE ICDM 2024)
|
NSF
|
08/15/2024
|
07/31/2025
| 25,000 | 25,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
|
{'SignBlockName': 'Sylvia Spengler', 'PO_EMAI': 'sspengle@nsf.gov', 'PO_PHON': '7032927347'}
|
The IEEE International Conference on Data Mining (ICDM) has established itself as the world’s premier research conference in data mining. It provides an international forum for the presentation of original research results and the exchange and dissemination of innovative and practical development experiences. The conference covers all aspects of data mining, including algorithms, software, systems, and applications. Student travel awards permit full participation by those who are primary authors on accepted papers. A PhD forum and a Women in Science Research Forum are part of the agenda, and will help early career researchers to learn and exchange cutting-edge research ideas and help them communicate on different aspects of career development.<br/><br/>Data mining and machine learning are now being broadly applied to nearly all disciplines, transforming science, engineering, medicine, healthcare, finance, business, and ultimately society itself. The award will be used to provide travel support for students and early career researchers, with a special focus on women and minorities, for the following activities: 1) To help fund the travel of Ph.D. students who are primary authors of full papers that have been accepted to the technical program; 2) To help fund the travel of Ph.D. students who are participating in the Ph.D. Student Forum; and 3) To help cover the travel expenses of women researchers to participate in the Women in Science Research Forum. This proposal aims to provide the crucial funding needed to support the participation of graduate students and early career researchers who will become future leaders in the science and engineering field. As an effort to engage young researchers, the IEEE ICDM 2024 will involve them in the meeting organization and include mentoring activities in the conference program.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/28/2024
|
07/28/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2440725
|
{'FirstName': 'Yi', 'LastName': 'He', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yi He', 'EmailAddress': 'yihe@cs.odu.edu', 'NSF_ID': '000875245', 'StartDate': '07/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'College of William and Mary', 'CityName': 'WILLIAMSBURG', 'ZipCode': '231852817', 'PhoneNumber': '7572213965', 'StreetAddress': '1314 S MOUNT VERNON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'VA01', 'ORG_UEI_NUM': 'EVWJPCY6AD97', 'ORG_LGL_BUS_NAME': 'COLLEGE OF WILLIAM AND MARY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'College of William and Mary', 'CityName': 'WILLIAMSBURG', 'StateCode': 'VA', 'ZipCode': '231852817', 'StreetAddress': '1314 S MOUNT VERNON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'VA01'}
|
{'Code': '736400', 'Text': 'Info Integration & Informatics'}
|
2024~25000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2440725.xml'}
|
EAGER: SupplyChainDCL: Exploring Collaborative Incentive Structures for Sharing Cost of Resilience in Supply Chains
|
NSF
|
02/01/2025
|
01/31/2027
| 238,149 | 238,149 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Georgia-Ann Klutke', 'PO_EMAI': 'gaklutke@nsf.gov', 'PO_PHON': '7032922443'}
|
This EArly-concept Grant for Exploratory Research (EAGER) award will contribute to the prosperity and welfare of the nation’s defense and commercial industrial base by developing an innovating framework for strengthening supply chain of critical minerals. The US is 100 percent reliant on imports for at least 12 key minerals deemed critical by the US government, increasing exposure to a number of natural and geopolitical risks. These minerals play a significant role in developing products important to renewable energy and defense technologies, among other important sectors. Using the supply chain for manganese as a test case, this project will study strategies for companies in a distributed supply chain to form alliances to ensure continuity of product flow by promoting supplier stability and decreasing single source dependencies. Currently, supply chain participants act in self-interest for profit maximization, leading to potential inefficiencies in ensuring functionality and performance of the entire supply chain. By engaging in alliances via shared costs, the potential exists to reduce exposure to demand and price fluctuations and raw material supply disruptions and to improve supply chain performance. Such strategies place a premium on stable sourcing as opposed to low-cost sourcing and incentivize all supply chain participants to ensure end market product availability. The project develops new models and utility functions to quantify the value, benefit and cost associated with companies engaging in strategic cooperation. Additionally, the project will offer mechanisms to control commodity price volatility using financial instruments such as offtake agreements and minimum guaranteed purchase prices. The results of this research will offer a blueprint for companies to form associations and alliances with each other that encourage risk sharing among supply chain partners and offer a fair way of allocating the cost of resilience among them. This award will support the involvement of a graduate student and undergraduate student to advance the research agenda.<br/><br/>This project will develop a framework wherein companies in a supply chain are viewed as players in a cooperative game. Collaboration among two or more players of groups are called coalitions where the assertion that the maximum benefit of cooperation can be realized by partaking in the grand coalition (group of all players) will be assessed. Notably, the study will quantify the cost of resilience defined as additional capacity built into the supply chain network by means of chaining and containment that offers benefit of stability to all entities in the network. The project focuses on developing fair cost allocation schemes using proportional allocations methods and advanced game-theoretic methods such as Shapley Value and Least Core. Novel optimization approaches are employed to enforce fairness as constraints of the model during cost allocation with the goal of maximizing the incentive to participate in a grand coalition for each company. Profit and Loss functions for players are developed using method of least squares comprising of linear and non-linear regression. These cost functions will predict commodity prices based on the value of the refined product in the open market, which in turn will serve as an indicator of viability in cooperation among players in the game. The project will validate methods by conducting a case study on purchase and sale of manganese and its refined products with its largest application area in the steel industry.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/05/2024
|
08/05/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2440850
|
{'FirstName': 'Saurav', 'LastName': 'Kumar Dubey', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Saurav Kumar Dubey', 'EmailAddress': 'kumardubey@ksu.edu', 'NSF_ID': '000785275', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Kansas State University', 'CityName': 'MANHATTAN', 'ZipCode': '665062504', 'PhoneNumber': '7855326804', 'StreetAddress': '1601 VATTIER STREET', 'StreetAddress2': '103 FAIRCHILD HALL', 'CountryName': 'United States', 'StateName': 'Kansas', 'StateCode': 'KS', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'KS01', 'ORG_UEI_NUM': 'CFMMM5JM7HJ9', 'ORG_LGL_BUS_NAME': 'KANSAS STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'Kansas State University', 'CityName': 'MANHATTAN', 'StateCode': 'KS', 'ZipCode': '665062504', 'StreetAddress': '1601 VATTIER STREET', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Kansas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'KS01'}
|
{'Code': '006Y00', 'Text': 'OE Operations Engineering'}
|
2024~238149
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2440850.xml'}
|
A Granular Framework for Assessing the Incidence of Local Economic Shocks
|
NSF
|
08/01/2024
|
07/31/2025
| 423,000 | 107,388 |
{'Value': 'Standard Grant'}
|
{'Code': '04050000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}
|
{'SignBlockName': 'Nancy Lutz', 'PO_EMAI': 'nlutz@nsf.gov', 'PO_PHON': '7032927280'}
|
Abstract<br/><br/>Urban economy models are challenged by a growing body of increasingly fine spatial data. This project develops a framework for the analysis of urban policies that accounts for geographically fine data. The project assembles data of new plant and office openings and combines them with commuting and land price information to analyze the predictions of quantitative spatial models. The project will provide new directions for the development of urban economy models. These models are useful for policy makers in their forecasts and evaluation of the effects of changes to the economic environment.<br/><br/>Conventional quantitative spatial models assume a continuum of agents. Therefore, conventional estimation procedures may over-fit granular outcomes due to sampling noise. This project develops a granular spatial-equilibrium model that features the optimizing decisions of a finite number of individuals, as well as land and labor market clearing, leading to endogenous prices for land and labor. The project empirically implements the model and illustrates advances over prior econometric approaches. Furthermore, by collecting and utilizing data on plant and office openings and commuting and land price responses, the project evaluates predictions of spatial economic models. These models have become increasingly popular in economic analysis and evaluating their predictions will increase the confidence in their predictions and lead to future research on these frameworks.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/26/2024
|
08/26/2024
|
None
|
Grant
|
47.075
|
1
|
4900
|
4900
|
2440877
|
{'FirstName': 'Felix', 'LastName': 'Tintelnot', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Felix Tintelnot', 'EmailAddress': 'tintelnot@uchicago.edu', 'NSF_ID': '000675705', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'National Bureau of Economic Research Inc', 'CityName': 'CAMBRIDGE', 'ZipCode': '021385359', 'PhoneNumber': '6178683900', 'StreetAddress': '1050 MASSACHUSETTS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MA05', 'ORG_UEI_NUM': 'GT28BRBA2Q49', 'ORG_LGL_BUS_NAME': 'NATIONAL BUREAU OF ECONOMIC RESEARCH INC', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'National Bureau of Economic Research Inc', 'CityName': 'CAMBRIDGE', 'StateCode': 'MA', 'ZipCode': '021385359', 'StreetAddress': '1050 MASSACHUSETTS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MA05'}
|
{'Code': '132000', 'Text': 'Economics'}
|
2020~107388
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2440877.xml'}
|
Conference: NAIRR Software Workshop
|
NSF
|
09/01/2024
|
08/31/2025
| 99,739 | 99,739 |
{'Value': 'Standard Grant'}
|
{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}
|
{'SignBlockName': 'Sheikh Ghafoor', 'PO_EMAI': 'sghafoor@nsf.gov', 'PO_PHON': '7032927116'}
|
The National AI Research Resource (NAIRR) workshop aims to establish an accessible AI software stack that democratizes AI capabilities and empowers diverse users. By bringing together academics, researchers, and industry experts, the workshop will address immediate and long-term objectives for the NAIRR pilot, pinpointing critical components for various scientific research domains. Focus areas will include real-time data analysis, AI-based decision-making, privacy, security, and software portability across emerging AI hardware platforms. This collaborative effort is designed to ensure that the resulting AI software stack meets the needs of a broad spectrum of users, from beginners to experts, fostering an inclusive AI ecosystem.<br/><br/>The workshop's outcomes will emphasize the creation of ethical, transparent, and trustworthy AI software tailored for scientific research. The workshop aims to foster innovation, enhance diversity, and ensure equitable access to AI resources by leveraging existing software stacks from academia, national laboratories, and industry. Discussions will address user-support needs, funding requirements, and procedures for incorporating new software developments into the NAIRR stack. The workshop will culminate in the production of a comprehensive report detailing the necessary AI software stack to serve users ranging from beginners to experts, thereby fostering an inclusive AI ecosystem. This effort will lay the foundation for a robust, democratized AI research infrastructure, driving innovation across the U.S. AI landscape.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/31/2024
|
07/31/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2440948
|
[{'FirstName': 'Dhabaleswar', 'LastName': 'Panda', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dhabaleswar K Panda', 'EmailAddress': 'panda@cse.ohio-state.edu', 'NSF_ID': '000487085', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Michael', 'LastName': 'Papka', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael E Papka', 'EmailAddress': 'papka@uic.edu', 'NSF_ID': '000311964', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]
|
{'Name': 'University of Illinois at Chicago', 'CityName': 'CHICAGO', 'ZipCode': '606124305', 'PhoneNumber': '3129962862', 'StreetAddress': '809 S MARSHFIELD AVE M/C 551', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'IL07', 'ORG_UEI_NUM': 'W8XEAJDKMXH3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ILLINOIS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Illinois at Chicago', 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606124305', 'StreetAddress': '809 S MARSHFIELD AVE M/C 551', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'IL07'}
|
{'Code': '296Y00', 'Text': 'NAIRR-Nat AI Research Resource'}
|
2024~99739
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2440948.xml'}
|
Collaborative Research: Ideas Lab: The Role of Extracellular RNA in Intercellular and Interkingdom Communication
|
NSF
|
03/01/2024
|
02/28/2027
| 1,022,597 | 876,898 |
{'Value': 'Standard Grant'}
|
{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}
|
{'SignBlockName': 'Gerald Schoenknecht', 'PO_EMAI': 'gschoenk@nsf.gov', 'PO_PHON': '7032925076'}
|
This project is a collaboration among seven laboratories with diverse and complementary expertise. The overarching goal of the project is to understand the role of extracellular RNA (exRNA) in communication between cells and in shaping the community of microbes, especially bacteria, that live on and inside plants, insects, and humans. These collections of microbes are often referred to as microbiomes and are critical for the health of plants and animals, including humans. A healthy microbiome promotes a healthy immune system, but how healthy microbiomes are maintained is poorly understood. This project will test the hypothesis that RNA secreted by host cells plays a central role in maintaining health both through communication among cells and by modifying the microbiome. RNA is best known for its key role in protein production inside cells, such as in RNA-based COVID vaccines. However, not all RNA encodes proteins, and cells produce more non-coding RNA than coding RNA, some of which is actively pushed into the environment by cells. This secreted RNA appears to be taken up by other cells, including bacteria and fungi, where it could potentially impact their growth. Understanding how exRNAs shape communication between cells and organisms will enable manipulation of exRNA communication in both agriculture and medicine, which will lead to development of environmentally friendly pesticides, as well as treatments that promote formation of healthy microbiomes in both plants and animals. This knowledge will also enable development of diagnostic and therapeutic tools for early detection and/or treatment of disease.<br/><br/>All cellular organisms secrete RNAs. The functions of these extracellular RNAs (exRNAs), however, are poorly understood. Two likely functions are intercellular and interkingdom communication. Open questions abound in exRNA biology: how are exRNAs selected for secretion, how are they targeted to recipient cells, and what are their roles in normal health and organismal fitness? Arabidopsis leaf exRNA isolates are highly enriched in the post-transcriptional modification N6-methyladenosine (m6A) (as compared to total cellular RNA) suggesting that post-transcriptional modifications may tag specific RNAs for export. Consistent with this, human exosomal microRNAs are enriched with m6A (relative to cytosolic microRNAs). Interestingly, a large number of mammalian small non-coding RNAs (ncRNAs) that localize to the external cell surface were recently found to harbor specific sialylated glycan modifications. These observations suggest that specific RNA modifications tag RNAs for cellular export and direct entry into appropriate recipient cells. This project will 1) test the hypothesis that exRNAs have specific features marking them for secretion and uptake, both within and among species, 2) determine how exRNAs are transferred from signaler to receiver cells, and 3) assess the impact of exRNA on microbiome health and composition through examining human gut, insect gut, and leaf surface models.<br/><br/>This project was co-funded by the Directorate for Biological Sciences, and the Plant Genome Research Program and the Plant Biotic Interactions Program in the Division of Integrative Organismal Systems.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/06/2024
|
08/06/2024
|
None
|
Grant
|
47.074
|
1
|
4900
|
4900
|
2441478
|
{'FirstName': 'Patricia', 'LastName': 'Baldrich', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Patricia Baldrich', 'EmailAddress': 'pbaldrich@ucdavis.edu', 'NSF_ID': '000818465', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of California-Davis', 'CityName': 'DAVIS', 'ZipCode': '956186153', 'PhoneNumber': '5307547700', 'StreetAddress': '1850 RESEARCH PARK DR STE 300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'CA04', 'ORG_UEI_NUM': 'TX2DAGQPENZ5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, DAVIS', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of California-Davis', 'CityName': 'DAVIS', 'StateCode': 'CA', 'ZipCode': '956186153', 'StreetAddress': '1850 RESEARCH PARK DR STE 300', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'CA04'}
|
[{'Code': '132900', 'Text': 'Plant Genome Research Project'}, {'Code': '727500', 'Text': 'Cross-BIO Activities'}]
|
2023~876897
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2441478.xml'}
|
Permutations in Random Geometry
|
NSF
|
08/01/2024
|
05/31/2027
| 180,000 | 43,582 |
{'Value': 'Continuing Grant'}
|
{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
|
{'SignBlockName': 'Elizabeth Wilmer', 'PO_EMAI': 'ewilmer@nsf.gov', 'PO_PHON': '7032927021'}
|
This project lies at the intersection of probability theory, combinatorics, and mathematical physics. Its primary objective is to uncover novel connections between two currently active research domains that have developed independently until recently: random permutations and random geometry. The emerging interplay between permutons (limits of random permutations) and random geometric objects arising in quantum physics and statistical mechanics (such as Schramm–Loewner evolution curves and Liouville quantum gravity surfaces) will play a fundamental role in generating significant advancements in both fields. This will involve formulating novel theories for universal random permutons and random directed metrics, expanding existing ones, and effectively resolving long-standing problems on meanders and meandric systems. <br/><br/>The three main objectives of this research project are, first, to investigate the problem of the longest increasing subsequence of random permutations from a novel angle, which involves linking it to directed metrics in planar maps. The goal is to construct a 'quantum version' of the universal Kardar-Parisi-Zhang geometry, i.e., the directed landscape. Second, to study the geometry of random meanders and broader statistical physics models involving crossing fully packed loops on planar maps. The objective is to tackle the long-standing open problem of determining the scaling limit of random uniform meanders and meandric permutations. Third to establish connections between the limits of d-dimensional permutations and new scale-invariant d-dimensional random geometries introduced in the physical literature. The aim is to begin developing a novel d-dimensional theory of random geometries and permutons. The project offers opportunities for education and outreach to high school and undergraduate students, as well as mentoring of undergraduate and Ph.D. students.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
07/25/2024
|
07/25/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2441646
|
{'FirstName': 'Jacopo', 'LastName': 'Borga', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jacopo Borga', 'EmailAddress': 'jborga@mit.edu', 'NSF_ID': '000889565', 'StartDate': '07/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'ZipCode': '021394301', 'PhoneNumber': '6172531000', 'StreetAddress': '77 MASSACHUSETTS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'E2NYLCDML6V1', 'ORG_LGL_BUS_NAME': 'MASSACHUSETTS INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': 'E2NYLCDML6V1'}
|
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'StateCode': 'MA', 'ZipCode': '021394301', 'StreetAddress': '77 MASSACHUSETTS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}
|
{'Code': '126300', 'Text': 'PROBABILITY'}
|
2024~43582
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2441646.xml'}
|
Support for Broadening Student Participation in the 2024 Modeling, Estimation, and Control Conference (MECC 2024); Chicago, Illinois; 27-30 October 2024
|
NSF
|
09/01/2024
|
08/31/2025
| 20,000 | 20,000 |
{'Value': 'Standard Grant'}
|
{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}
|
{'SignBlockName': 'Yue Wang', 'PO_EMAI': 'yuewang@nsf.gov', 'PO_PHON': '7032924588'}
|
This grant provides support for broadening student participation at the 2024 Modeling, Estimation, and Control Conference (MECC 2024) in Chicago, Illinois, 27-30 October 2024. Held annually since 2021, MECC focuses on the intertwined research problems of building mathematical models of dynamic systems, fitting these models to measured data, and using the models for control algorithm design. The scope of the conference encompasses theoretical research as well as a broad range of applications, including the automatic control of (ground, air, marine, and space) vehicles, transportation networks, power/energy systems, robots, and biomedical systems, to name some examples. MECC is predominantly an academic research conference, with most attendees either seeking or already having doctoral degrees. The overarching goal of this grant is to broaden this audience significantly by recruiting and engaging K-12, undergraduate, and early-career graduate students. This recruitment effort will focus predominantly on students who have never attended a control conference before, with the goal of making the conference more accessible to female and underrepresented minority students.<br/><br/>Three education and outreach events will be created as part of this grant. These events will focus on introducing student participants to the automatic control discipline in general, its application to scaled autonomous vehicles, and its interplay with embedded computing. The speakers at these events will include a mix of researchers and practitioners from both academia and industry. Students will be recruited to these events from universities nationwide, as well as from a broad range of K-12 schools in the Chicago area. A panel of judges will select at least 40 of these students for support through this grant, with an emphasis on expanding conference participation and accessibility to a broad range of student participants. Funding will be used for supporting the students’ travel to the conference, providing them with access to take-home kits for their continued learning, and supporting the participation of a diverse range of speakers at the above three events. A key goal of these efforts will be to transform MECC itself, from an academic research conference to an event that brings research and teaching much closer together. Such a transformation will benefit all conference participants. It will broaden access to the conference by engaging a more diverse student population. It will also give the traditional conference attendees more of a chance to discuss both the intellectual merit of their research as well as the broader impact of this research, particularly given the broader and more diverse audience.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2441747
|
{'FirstName': 'Hosam', 'LastName': 'Fathy', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hosam Fathy', 'EmailAddress': 'hfathy@umd.edu', 'NSF_ID': '000408155', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'ZipCode': '207425100', 'PhoneNumber': '3014056269', 'StreetAddress': '3112 LEE BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MD04', 'ORG_UEI_NUM': 'NPU8ULVAAS23', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, COLLEGE PARK', 'ORG_PRNT_UEI_NUM': 'NPU8ULVAAS23'}
|
{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'StateCode': 'MD', 'ZipCode': '207425100', 'StreetAddress': '3112 LEE BUILDING', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MD04'}
|
{'Code': '756900', 'Text': 'Dynamics, Control and System D'}
|
2024~20000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2441747.xml'}
|
Coordination for the Migration Collaborative Research Action (C-MiCRA)
|
NSF
|
08/15/2024
|
07/31/2027
| 1,107,695 | 839,941 |
{'Value': 'Continuing Grant'}
|
{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}
|
{'SignBlockName': 'Lina Patino', 'PO_EMAI': 'lpatino@nsf.gov', 'PO_PHON': '7032925047'}
|
Through this award, Future Earth supports projects funded under the Belmont Forum Collaborative Research Action “Integrated Approaches to Human Migration/Mobility in an Era of Rapid Global Change”. The awardee will coordinate research, synthesis, communication, capacity building and mobilizing as well as valorization for the transdisciplinary international research teams. By coordinating teams and fostering cross-team synthesis, Future Earth will leverage research support, and build integrated knowledge and tools that reach a broad range of actors in the public and private sector focused on migration and mobility issues. The capacity building efforts will provide science leadership support to awardees around the globe, and assist teams in the difficult process of engaging with non-scientists in transdisciplinary research. Future Earth will bring together awardees at the transdisciplinary international meetings to further promote the integration of the new awardees.<br/><br/>Future Earth will implement an interactive, reflexive post-award coordination agenda for the Belmont Forum’s collaborative research action on Migration. Belmont Forum’s programs award grants, distributed in international, transdisciplinary teams, in order to bring together the fragmented research and innovation expertise across the globe to find innovative new solutions to their challenge. These teams include researchers and partners from universities, research centers, civil society organizations, community organizations, and the private sectors. The aim of the Migration call is to develop projects illuminating the determinants of migration - why people move, do not move, from and to where and when, and on what time scale, in relation to Global Change processes like environmental and climate change, demographic changes, consumption patterns, energy use and land-use. The capacity of the research teams to reach their aims will depend, to a great extent, on the degree to which their work can be integrated and supported. Future Earth will carry out the coordination, valorization and synthesis, partnering with two international organizations. The Global Development Network to support capacity building, mentoring and communication, and the Engineering Center for System Solutions will support the development of simulations to functionally integrate the diversity of perspectives, strengthen participation processes, develop effective communication and cooperation skills, explore the governance of social-ecological systems, and support mindset and behavioral change.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/08/2024
|
08/08/2024
|
None
|
Grant
|
47.050
|
1
|
4900
|
4900
|
2441820
|
[{'FirstName': 'Judit', 'LastName': 'Ungvari', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Judit Ungvari', 'EmailAddress': 'judit.ungvari@futureearth.org', 'NSF_ID': '000765368', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Makyba', 'LastName': 'Charles-Ayinde', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Makyba Charles-Ayinde', 'EmailAddress': 'makyba.charles-ayinde@futureearth.org', 'NSF_ID': '0000A09JK', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]
|
{'Name': 'FUTURE EARTH', 'CityName': 'FORT COLLINS', 'ZipCode': '805263602', 'PhoneNumber': '9704305946', 'StreetAddress': '413 CHUKAR CT', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Colorado', 'StateCode': 'CO', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'CO02', 'ORG_UEI_NUM': 'L7TZMMZ98BQ4', 'ORG_LGL_BUS_NAME': 'FUTURE EARTH', 'ORG_PRNT_UEI_NUM': 'WKLBHVNBACE3'}
|
{'Name': 'FUTURE EARTH', 'CityName': 'FORT COLLINS', 'StateCode': 'CO', 'ZipCode': '805263602', 'StreetAddress': '413 CHUKAR CT', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Colorado', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'CO02'}
|
{'Code': '731300', 'Text': 'Intl Global Change Res & Coord'}
|
2024~839941
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2441820.xml'}
|
EAGER: Exploring the Carbon Footprint Reporting Approaches for National Computing Research Infrastructure
|
NSF
|
09/01/2024
|
08/31/2026
| 300,000 | 300,000 |
{'Value': 'Standard Grant'}
|
{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}
|
{'SignBlockName': 'Edward Walker', 'PO_EMAI': 'edwalker@nsf.gov', 'PO_PHON': '7032924863'}
|
The environmental impact of computing has raised concerns worldwide as the growth of both Artificial Intelligence (AI) and Cloud Computing continues to accelerate. These trends are exacerbated by the slowing energy-efficiency improvement of computing technology. Organizations that procure and operate computing equipment are increasingly viewed as accountable for the carbon-emissions impact, water use, and other environmental costs of computing. Yet today, there are few clear reporting standards for what can be practically done with a reasonable effort. In short, while the need is clear, there is a lack of clear pathways and practices. The project will develop recommendations for effective climate impact reporting at scientific research computing centers, with an accompanying community engagement plan to ensure broad adoption.<br/><br/>The project proposes to analyze existing proposals and practices for reporting on the environmental damage caused by large-scale research computing. The study will explore and develop a range of methodologies for assessing carbon footprint (embodied, operational, and after-use) and other environmental impacts such as water use. The initial focus will be on facilities operated by academic institutions and government-funded centers. An important part of the study includes the engagement of the community that operates such systems to understand the effort required to produce rigorous reporting and the tradeoff between effort and accuracy. The plan is to engage the academic computing community collaboratively to create realistic, implementable reporting options. The project's hypothesis is that broad adoption of the proposed reporting methods, and accessibility to the accompanying data used in reporting, will lead to procurement, operation, and disposal practices that reduce environmental damage from scientific research computing.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/13/2024
|
08/13/2024
|
None
|
Grant
|
47.070
|
1
|
4900
|
4900
|
2442555
|
{'FirstName': 'Andrew', 'LastName': 'Chien', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andrew A Chien', 'EmailAddress': 'achien@cs.uchicago.edu', 'NSF_ID': '000295194', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Chicago', 'CityName': 'CHICAGO', 'ZipCode': '606375418', 'PhoneNumber': '7737028669', 'StreetAddress': '5801 S ELLIS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'IL01', 'ORG_UEI_NUM': 'ZUE9HKT2CLC9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CHICAGO', 'ORG_PRNT_UEI_NUM': 'ZUE9HKT2CLC9'}
|
{'Name': 'University of Chicago', 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606375418', 'StreetAddress': '5801 S ELLIS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'IL01'}
|
{'Code': '723100', 'Text': 'CYBERINFRASTRUCTURE'}
|
2024~300000
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2442555.xml'}
|
RAPID: Accelerated Deployment of EDGES for Cosmic Dawn Observations
|
NSF
|
08/15/2024
|
07/31/2025
| 187,021 | 187,021 |
{'Value': 'Standard Grant'}
|
{'Code': '03020000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'AST', 'LongName': 'Division Of Astronomical Sciences'}}
|
{'SignBlockName': 'Nigel Sharp', 'PO_EMAI': 'nsharp@nsf.gov', 'PO_PHON': '7032924905'}
|
This project is a highly targeted, urgent and short-term continuation of an existing program which studies the early Universe by deploying instrumentation to remote, radio-quiet locations. This enables sensitive observations with unprecedented absolute calibration. The current observations are being made from a remote location in Australia. The next step is to repeat the Australian measurement from the northern hemisphere, but this is already seriously compromised and may become impossible, due to rapidly strengthening anomalous emission near 63 MHz. It is urgent to deploy equipment during the 2024/25 winter season and take measurements before this interference comes to dominate. As there is evidence the signal comes from satellites in low earth orbit, the PI and team will also be working with the probable operator, to characterize, identify, and mitigate the spurious emission, in close coordination with the NSF Spectrum Management Office. This work is of strong practical utility world-wide, will raise awareness of unintended science impacts from industrial efforts, and forge connections with remote communities, helping scientific use of extraordinary locations.<br/><br/>The need for urgent action is a swiftly deteriorating global RFI situation due to satellite mega-constellations, which cannot be avoided by relocating, and which threaten to make this measurement soon impossible from anywhere on the surface of the Earth. The PI has identified a location from which to make the necessary observations: remote Adak island, 1930 km from the nearest substantial concentration of FM radio transmitters, is superior to the site in western Australia, and will provide long winter nights for data-gathering. The proposal describes other characteristics of this impressive site. This study is urgently needed to run these tests before the environmental changes render them impossible.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/14/2024
|
08/14/2024
|
None
|
Grant
|
47.049
|
1
|
4900
|
4900
|
2442745
|
{'FirstName': 'Colin', 'LastName': 'Lonsdale', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Colin J Lonsdale', 'EmailAddress': 'cjl@mit.edu', 'NSF_ID': '000205991', 'StartDate': '08/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'ZipCode': '021394301', 'PhoneNumber': '6172531000', 'StreetAddress': '77 MASSACHUSETTS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'E2NYLCDML6V1', 'ORG_LGL_BUS_NAME': 'MASSACHUSETTS INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': 'E2NYLCDML6V1'}
|
{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'StateCode': 'MA', 'ZipCode': '021394301', 'StreetAddress': '77 MASSACHUSETTS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}
|
[{'Code': '125700', 'Text': 'MID-SCALE INSTRUMENTATION'}, {'Code': '151Y00', 'Text': 'SII-Spectrum Innovation Initia'}]
|
2024~187021
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2442745.xml'}
|
ECO-CBET: GOALI: CAS-Climate: Expediting Decarbonization of Cement Industry through Integration of CO2 Capture and Conversion
|
NSF
|
01/01/2024
|
12/31/2026
| 1,695,614 | 480,829 |
{'Value': 'Continuing Grant'}
|
{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}
|
{'SignBlockName': 'Bruce Hamilton', 'PO_EMAI': 'bhamilto@nsf.gov', 'PO_PHON': '7032920000'}
|
The overall goal of this project is to deliver an innovative, integrated, and adaptable CO2 capture-conversion system to enable decarbonization of the cement industry while producing valuable cement supplements from waste CO2. In transitioning to a net-zero emission and circular economy, waste CO2 in industrial flue gases is considered as a valuable resource for production of a wide range of value-added products. Cutting America’s CO2 emissions in half by 2030 requires investment in industry sectors like cement that cannot shift entirely to carbon-free energy sources just yet. The U.S. is currently producing ~90 million tons of cement every year, emitting nearly the same amount of CO2. If no eco-efficient alternative cements can be invented to completely replace Portland cement, a promising strategy to decarbonize the cement industry in the foreseeable future is to transform Portland cement into blended cement. In this project, the approach is to capture CO2 from cement flue gas and use it as a renewable feedstock to produce blended cement using carbon-negatively processed industrial wastes. The proposed capture-conversion technology will be integrated into a cement production unit, where the CO2 comes from the flue gas of the cooler end of the kiln, and the waste materials and waste heat from the cement plant can be used to run the CO2 conversion process.<br/> <br/>The project team will explore the fundamental chemistry needed to develop economically viable technology to convert the captured CO2 to blended cement. The fundamental findings at the molecular level (reaction chemistry and sorbent development) will be merged with extensive process modeling, simulation, and design optimization, along with techno-economic analysis (TEA) and rigorous life cycle assessment (LCA) of representative cement manufacturing facilities with and without the integration of the CO2 capture-conversion process. The team will leverage convergence science principles to advance the scientific, technological, and socio-economic knowledge needed to overcome challenges associated with: 1) CO2 capture, 2) CO2 conversion, 3) process systems engineering and integration, and 4) environmental sustainability assessment for expediting the decarbonization of the cement industry. The project has the potential to open new opportunities for achieving net-zero CO2 emissions from the cement industry while producing a valuable cement supplement from waste resources (e.g., alkali industrial wastes such as off-specification coal ashes). Assuming broad technology adoption and replication, potential profitable CO2 emission reductions of >50 Mt/year are projected for U.S., the possibility of which is enhanced by collaboration with the Ash Grove Cement Company. Components of the collaboration with the Ash Grove partner include graduate student summer internships and seminars on CO2 capture-conversion by both University researchers and Ash Grove engineers.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|
08/23/2024
|
08/23/2024
|
None
|
Grant
|
47.041
|
1
|
4900
|
4900
|
2442910
|
{'FirstName': 'Fateme', 'LastName': 'Rezaei', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Fateme Rezaei', 'EmailAddress': 'rezaeif@miami.edu', 'NSF_ID': '000680092', 'StartDate': '08/23/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
|
{'Name': 'University of Miami', 'CityName': 'CORAL GABLES', 'ZipCode': '331462919', 'PhoneNumber': '3052843924', 'StreetAddress': '1320 SOUTH DIXIE HIGHWAY STE 650', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '27', 'CONGRESS_DISTRICT_ORG': 'FL27', 'ORG_UEI_NUM': 'RQMFJGDTQ5V3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MIAMI', 'ORG_PRNT_UEI_NUM': None}
|
{'Name': 'University of Miami', 'CityName': 'CORAL GABLES', 'StateCode': 'FL', 'ZipCode': '331462919', 'StreetAddress': '1320 SOUTH DIXIE HIGHWAY STE 650', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '27', 'CONGRESS_DISTRICT_PERF': 'FL27'}
|
{'Code': '172Y00', 'Text': 'ECO-CBET'}
|
2022~480829
|
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2442910.xml'}
|
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