Project Grant 2502282
- The National Science Foundation (NSF) Engineering program (CFDA 47.041) has awarded a $100,000 Project Grant to the University of Washington (UW) for the "Collaborative Research: MFAI: Mathematical Frontiers of Generative AI" project. The grant, awarded on September 1, 2025, aims to uncover the mathematical principles that explain the effectiveness of advanced generative AI models, including large language models, and to overcome the limitations of current brute-force approaches. The...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides funding of $296,023 to establish the mathematical foundations of two key models used in generative artificial intelligence (AI) methodologies. The primary goals are to: Examine the generative capabilities of score-based generative models in high dimensions and understand the predictive capabilities and limitations of transformer-based foundation models for...
- This $218,771 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to develop new theoretical tools to enhance flow-based generative artificial intelligence (AI) models. The research aims to elucidate how these models, including diffusion models, produce novel outputs and extend their capabilities to handle complex data types beyond the Euclidean setting, such as graphs and point clouds. The project,...
- This $100,000 Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research to elucidate the fundamental mechanisms underlying flow-based generative AI models, such as diffusion models, and extend their capabilities to handle complex data types. The research aims to: (1) understand why trained flow models often generalize better than theoretically expected, using tools from geometry, ODE, manifold learning, and deep learning theory; and (2)...
- This federal Project Grant award of $100,000.00, provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program, supports research on advanced probabilistic models and their application to cutting-edge machine learning techniques. The research aims to bring mathematical rigor and develop new methods related to complex systems in areas such as image processing, reinforcement learning, and generative AI. Key focus areas include: 1) extracting...
- The National Science Foundation (NSF) awarded a $163,000 Project Grant under the Mathematical and Physical Sciences grant program (CFDA 47.049) to The Trustees of Columbia University in the City of New York. The goal of this 3-year research project is to build mathematical foundations for understanding the behavior and limitations of modern machine learning systems, with a focus on how AI models represent and learn from data. The research aims to develop general principles for how features...
- The National Science Foundation (NSF) awarded a $300,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of Wisconsin System for the project "Collaborative Research: III Small: Towards Large Open-World Foundation Models: Construction, Adaptation, and Deployment." The project, running from August 1, 2025 to July 31, 2028, aims to develop new algorithms, theorems, and systems to improve the reliability of advanced artificial...
- This $471,529 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to expand the understanding of large language models (LLMs), a type of artificial intelligence (AI). The project at the Trustees of Boston University aims to move beyond identifying simple, binary concepts within LLMs and instead develop methods to discover and characterize more sophisticated, multi-dimensional...
- This $400,000 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports the development of a new framework and tools for advancing data-centric artificial intelligence (AI) through generative approaches to feature space reconstruction. The project aims to transform the traditional way of constructing feature spaces by using deep generative learning instead of manual or classical discrete search...
- This three-year $800,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to advance understanding of large language models through mathematical and conceptual analysis. The Trustees of Princeton University will receive funding to develop simplified generative text models, analyze how language models are trained on such generated texts, examine why learned models can perform downstream tasks, and design new adaptation methods with...
This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program provides $100,000 to the University of Wisconsin System to conduct research on the mathematical foundations of advanced generative AI models. The project aims to characterize the mathematical principles that underpin the effectiveness of frontier AI models, such as large language models, and identify key mathematical quantities driving their generalization capabilities. The research will focus on developing new theoretical frameworks, modeling approaches, and scaling laws to advance the capabilities of AI models for complex reasoning and problem-solving tasks. This work is intended to ensure the United States maintains global leadership in AI and drive progress in economic prosperity, national security, and global competitiveness.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $100.0k | 7/29/25 |