Project Grant 2521471
- This Project Grant award, valued at $325,000.00, was provided by the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program to the University of Washington. The project develops powerful new tools for understanding complex data, leveraging cutting-edge artificial intelligence (AI) techniques to help data analysts across diverse fields make informed, automated decisions. The research introduces novel approaches to analyze messy, heterogeneous, and large...
- This $175,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will fund research to develop new statistical and computational methods to enhance the reliability of data analysis in modern, large-scale datasets, particularly in the era of AI. The key areas of focus include: (1) analyzing the robustness of manifold and deep learning algorithms for high-dimensional, noisy, and nonlinear data; (2) developing statistical theory...
- This Project Grant award from the National Science Foundation (NSF) under CFDA 47.070 - Computer and Information Science and Engineering is for $395,927 over the period of Sep 1, 2024 to Aug 31, 2027. The award aims to develop theoretical and algorithmic foundations for building a safe and robust human-AI ecosystem, where machine learning (ML) and artificial intelligence (AI) techniques are used in applications involving humans, such as recommendation systems, lending, and healthcare. The key...
- The National Science Foundation awarded a $110,000 Project Grant under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program to Purdue University. The grant, titled "Collaborative Research: How AI Labor Research Influences Stakeholder Beliefs and Regulatory Preferences," examines how exposure to scholarly forecasts about the impact of artificial intelligence (AI) on labor markets shapes the perceptions, decision preferences, and intended behaviors of U.S. workers,...
- This Project Grant award of $194,675 from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports research to develop new econometric and statistical methods that allow researchers to draw valid conclusions from complex data in a variety of social, behavioral, and medical science settings. The key products and services to be delivered include: Developing a generally applicable reparameterization procedure for informative...
- This Project Grant award, totaling $252,798.00, was provided by the National Science Foundation (NSF) under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program. The award will fund a collaborative research project led by Yale University to analyze three linked questions: (i) how to price the tokens that govern access to large language models; (ii) how to design cloud-computing contracts that reward sustained but flexible demand; and (iii) how platforms can share and aggregate...
- This $285,000 federal Project Grant award from the National Science Foundation (NSF) Social, Behavioral, and Economic Sciences (SBE) program (CFDA 47.075) will fund research to develop new statistical methods to guide economic and public policy decisions in rapidly changing environments. The research aims to build on recent advances in statistical decision theory, causal inference, and machine learning to create econometric models that can effectively inform evidence-based policymaking while...
- This federal Project Grant award from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program provides $443,888 to the Research Foundation of the City University of New York (RFCUNY) to test theories of perceptual valuation using advanced machine learning and artificial intelligence (AI) techniques. The project aims to: 1) determine if deep neural network machine learning models can serve as proxies for people's internal models of visual objects, 2)...
- This Project Grant award, funded by the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program, supports a research project at Yale University that aims to understand the long-term impacts of neighborhood revitalization policies on individual and family economic outcomes. The $302,586 award, with a performance period from August 2025 to July 2028, will enable the researchers to systematically analyze historical records and administrative data using advanced...
- This $379,937 Project Grant from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports a computational research project at Yale University investigating how humans infer social relationships and group dynamics. The project aims to develop a theory and computational model of "structure learning" - the psychological processes that allow people to learn about social relationships by observing patterns of interaction between individuals....
This Project Grant award from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program provides funding of $307,273 to Yale University to develop new econometric methods and statistical theory to inform best practices for empirical researchers using data generated by artificial intelligence (AI) or machine learning (ML) algorithms. The research project aims to improve the validity of empirical research using AI- and ML-generated data by addressing bias and inference problems present in current practice. The project will contribute novel econometric methods and statistical theory for working with AI- and ML-generated data, including the development of appropriate asymptotic frameworks and efficiency theory for these modern data sources. The research outcomes will benefit businesses, non-profits, and government organizations by enhancing the quality of data analysis performed across various domains. The award period runs from August 15, 2025 to July 31, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $307.3k | 7/22/25 |