Project Grant 2502489
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) provides $150,000 to the University of Washington to conduct research into the mathematical foundations of advanced generative artificial intelligence (AI) models. The overarching goal is to uncover the mathematical principles underlying the remarkable performance of frontier AI models like large language models, in order to overcome current limitations and...
- This $296,023 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports research to establish the mathematical foundations of two models that underpin generative artificial intelligence (AI) methodologies in scientific contexts: score-based generative models and transformer-based foundation models. The primary goals of this 5-year project are to study the role of fine data structures in mitigating the curse of...
- This Project Grant award of $120,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program supports research to advance the mathematical foundations of generative artificial intelligence (AI) models, particularly diffusion models. The award enables researchers at the University of Missouri System to develop new theoretical tools to elucidate how flow-based generative models produce novel outputs and extend these models to...
- This $599,969 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) program aims to improve the scientific characterization of human preferences in the context of AI alignment. The principal objectives are to: 1) Develop a better understanding of how human preferences should be interpreted when used to train AI systems through reinforcement learning from human feedback (RLHF), and 2) Leverage this knowledge to practically...
- This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) provides $100,000.00 in funding to the University of Wisconsin System for the "Collaborative Research: MFAI: Mathematical Frontiers of Generative AI" project. The goal of this 3-year project, running from September 1, 2025 to August 31, 2028, is to uncover the mathematical principles underlying highly advanced...
- 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...
- This $450,000 Project Grant was awarded by the National Science Foundation (NSF) under the Engineering program (CFDA 47.041) to The Trustees of the University of Pennsylvania. The grant supports a collaborative U.S.-Swiss research project focused on developing novel theory and methods for effective, informed graph generation at scale. The key objectives of the project are to: (1) build discrete diffusion processes for progressively adding or removing edges from random graphs to reduce the...
- The National Science Foundation (NSF) awarded a 5-year, $119,764 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the Trustees of the University of Pennsylvania on June 1, 2025. The grant aims to develop formal specifications, verification frameworks, and certified artificial intelligence (AI) systems that can provide trustworthy and explainable reasoning behind model predictions. The project's key objectives are to bridge the gap between formal...
- This federal Project Grant award, valued at $450,000.00 and awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to address fundamental computational and statistical limitations of generative artificial intelligence (AI) methods. The key goals of the project are: Determine the capabilities and limitations of generative AI algorithms in terms of the types of probability distributions they can and cannot generate....
- This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) provides $100,000 to The Pennsylvania State University to develop an open, community-driven evaluation infrastructure for assessing the safety risks of large language models (LLMs). The project aims to advance AI safety research, foster public awareness, and strengthen workforce training in responsible AI practices. Key objectives include...
This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $500,000 in funding to The Trustees of the University of Pennsylvania, doing business as the Clinical Practices of the University of Pennsylvania, for research on the mathematical foundations of alignment in generative artificial intelligence (AI). The project aims to tackle the challenges of biases, unsafe outputs, and misleading content in large pretrained generative language and diffusion models by developing methods to better incorporate requirements such as fairness, safety, reliability, robustness, and truthfulness. The research will leverage properties of alignment problems in generative AI to simplify the technical approach. The project will run from October 1, 2025 to September 30, 2028.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $500.0k | 7/31/25 |