Cooperative Agreement 2505865
- 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 $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 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 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 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 $399,289 Project Grant awarded by the National Science Foundation (NSF) under the STEM Education program (CFDA 47.076) aims to advance the understanding of how generative artificial intelligence (GenAI) technologies can be effectively leveraged in undergraduate computer science education. The key objectives of this 2-year project are to: (a) critically examine how faculty are designing GenAI-based pedagogy and the resulting impacts on student learning, and (b) quantify the effects of...
- 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 $545,359 federal Project Grant was awarded by the National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) program to the University of Chicago. The grant will support the development of a new generation of artificial intelligence (AI) models designed to learn causal models and enable robust causal reasoning and meaningful abstraction in generative AI systems. The research aims to enhance the interpretability, verifiability, and real-world...
- 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 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Project Grant award provides $594,753 to Cornell University from September 1, 2025 to August 31, 2028 to develop novel methods for precisely controlling the outputs of generative artificial intelligence (AI) systems, such as text-generating chatbots and image creation tools. The research aims to address the critical problem of unpredictable and potentially unsafe outputs from these powerful AI...
This Cooperative Agreement award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program, with a total funding of $3,000,000, aims to advance the state of the art in generative artificial intelligence (AI). The primary goals are to develop broadly applicable foundational tools and new mathematical theories to address core algorithmic challenges in building and deploying large AI models. Key technical research thrusts include: 1) Algorithms and optimization for generative models, 2) A mathematical theory of foundation models, 3) Research on diffusion models for generative AI, and 4) Improving the robustness and safety of generative models. The award also includes use-inspired projects in medical imaging, generative biology, and AI for mathematical theorem-proving, with a focus on open-sourcing AI models for use across multiple domains. Additionally, the project will help thousands of students and working professionals acquire AI expertise through an online master's initiative and activities targeting high-school students.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $1.5m | 8/25/25 | ||
| Not listed | $1.0m | 8/25/25 | ||
| Not listed | $500.0k | 7/28/25 |