Project Grant 2301599
- This $346,500 three-year Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will fund research at The Ohio State University examining the long-term impacts of fair machine learning under strategic individual behavior. The researchers will establish an analytical framework to characterize complex sequential interactions between individuals and machine learning systems over repeated interactions. This framework aims to enable...
- This $331,698 National Science Foundation project grant supports research at Michigan State University to develop fair machine learning systems through improved data representations. Specifically, the Computer and Information Science and Engineering grant will fund research to study fundamental tradeoffs between utility and fairness in different data representations. The researchers will identify solutions to reduce gaps in achieving optimal tradeoffs and develop new representations and...
- This three-year, $300,000 project grant from the National Science Foundation's Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will support the development of new algorithms and computational methods for trustworthy machine learning via bi-level optimization. The grantee, Michigan State University, will advance the theoretical understanding and practical implementation of robust and fair deep learning....
- The Trustees of the University of Pennsylvania received a $392,992 Project Grant from the National Science Foundation Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070). The grant will support research and education activities aimed at developing machine learning techniques that break through the fairness-accuracy tradeoff paradigm. Specifically, the university researchers will draw on ideas from learning theory and...
- The National Science Foundation awarded $235,438 under the Computer and Information Science and Engineering federal grant program to develop interpretable and fair machine learning frameworks, algorithms, and methodologies. The two-year project grant aims to address concerns that machine learning algorithms can inadvertently amplify human biases by funding research to design scalable, data-driven methods with provable fairness guarantees. Specifically, the grant will support the development of...
- This three-year, $597,194 National Science Foundation project grant supports research at the Toyota Technological Institute at Chicago to advance the foundations of societal machine learning. The goals are to provide guarantees of fairness, accuracy, and positive societal impacts for machine learning systems used in applications impacting people. Key research areas include understanding fairness in machine learning contexts, especially regarding biased training data and multi-stage decisions;...
- This $400,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports research at The Ohio State University to develop theoretical and algorithmic foundations for building a safe and reliable human-AI ecosystem. The key objectives are to: 1) create an analytical framework to characterize human-AI interactions and safety components, 2) examine feedback effects between agents and the...
- This $625,000 National Science Foundation project grant supports research at the University of Maryland, College Park toward developing fair machine learning algorithms and applications. Specifically, the grant funds the "Toward Fair Decision Making and Resource Allocation with Application to AI-Assisted Graduate Admission and Degree Completion" project. The research aims to design artificial intelligence systems that make admission and resource allocation decisions for graduate...
- The National Science Foundation Division of Computing and Communication Foundations awarded Oberlin College $239,830 under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to support research from October 1, 2022 to September 30, 2025. The award will fund the development of a new theory of computational learning adapted to economic environments where participants may strategically manipulate data. Specifically, the research seeks to design algorithms...
- This $474,838 Project Grant was awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The grant, awarded to the University of Illinois, supports research addressing the triple challenges of accuracy, robust generalization, and interpretability in machine learning (ML) models. The key technical aims of the project include: (1) developing a unified framework for analyzing and optimizing the trade-offs...
This $253,472 National Science Foundation project grant supports research at The Ohio State University from November 2022 through September 2025 under the Computer and Information Science and Engineering program. The university will conduct a collaborative research project to rigorously model individual strategic behavior and its long-term impacts on the development of fair machine learning techniques. Specifically, the researchers will establish an analytical framework to characterize complex, sequential interactions between strategic individuals and machine learning systems over repeated interactions. This framework aims to enable rigorous analysis of how population dynamics evolve and could be leveraged to develop effective policy interventions improving social welfare and long-term equity. The university will analyze the proposed framework's robustness and accuracy through different experiments. The research's goals are to address fairness problems in machine learning and ensure the trustworthiness and responsible development of these technologies.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $253.5k | 10/21/22 |