Project Grant 2540120
- 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 $600,000 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program supports research by the University of Illinois to develop a theoretical control framework for understanding and improving diffusion-based generative machine learning models. The project aims to establish connections between generative modeling, optimal control theory, and partial/stochastic differential equations. Key technical objectives include enhancing...
- 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...
- This $218,771 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CFDA 47.070) program will enable research at the University of California, San Diego (UCSD) to enhance the mathematical foundations of artificial intelligence (AI). The research aims to (1) elucidate how flow-based generative models, including diffusion models, produce novel outputs, and (2) extend these models to handle complex data types beyond Euclidean spaces, such...
- 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 Project Grant award of $256,260.00 was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) Federal Grant Program. The grant, titled "CAREER: An Algorithmic Theory of Diffusion Models," seeks to develop a rigorous mathematical framework for understanding the effectiveness of diffusion models, a key component of generative artificial intelligence (AI). The project aims to advance machine learning theory by...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Project Grant award for $174,999 supports research on trustworthy diffusion models, a type of large generative artificial intelligence (AI) model. The key objectives are to improve the privacy, fairness, and explainability of these AI models, which are critical for their safe and ethical deployment in areas like healthcare, media, law, and education. The project involves implementing differential...
- This Project Grant award, provided by the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049), supports research exploring the statistical properties and capabilities of diffusion generative models, an emerging class of techniques for image and video synthesis, scientific simulation, and reinforcement learning. The $118,132 award, effective August 15, 2025 through July 31, 2028, will fund three key research objectives: (1) investigating the statistical...
- 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 Illinois. The 3-year grant, effective October 1, 2023, will fund research on reconstruction of diffusion history in cyber and human networks, with applications in epidemiology and cybersecurity. The research aims to develop fundamental theories and efficient, data-driven algorithms for identifying diffusion processes that best...
- 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...
The National Science Foundation (NSF) awarded a $299,997 Project Grant through its Computer and Information Science and Engineering (CISE) program to The University of Iowa. The grant, titled "EAGER: REVERSE DISCRETE TIME DIFFUSIONS: TRANSFORMING GENERATIVE AI," will fund research to develop a fundamental theory for directly reversing diffusion processes in generative AI models. This work aims to significantly improve the speed, accuracy, and efficiency of current generative AI algorithms that rely on indirect time reversal methods. The research project will run from October 1, 2025, to September 30, 2027, and is expected to constitute a foundational advance to the theory of diffusions, with broad implications for the field of generative AI.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $300.0k | 7/30/25 |