Project Grant 2602035
- The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded the Regents of the University of California (University of California, Berkeley) $500,000 on August 15, 2026, under the Engineering program (CFDA 47.041) to develop AI-enabled learning and control techniques for nonlinear systems operating in adversarial environments. The project addresses the vulnerability of complex dynamical systems—including power grids, autonomous vehicles, and other...
- The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded the Regents of the University of Michigan $150,000 on September 1, 2026, under the Engineering program (CFDA 47.041) to develop mathematical foundations for reinforcement learning and generative artificial intelligence systems. The project will use stochastic analysis, stochastic control, probability theory, and optimization to establish theory and algorithms for continuous-time reinforcement...
- The National Science Foundation Division of Computing and Communication Foundations awarded $800,000 under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to the University of California, Berkeley for a four-year collaborative research project grant. The project aims to improve the sample efficiency of reinforcement learning algorithms in both offline and online settings through techniques like optimistic exploration and pessimistic exploitation. It...
- The National Science Foundation Division of Civil, Mechanical, and Manufacturing Innovation awarded University of California Irvine $390,000 on October 1, 2026, under the Engineering program (CFDA 47.041) to develop control-theoretic foundations for trustworthy generative artificial intelligence in safety-critical engineering systems. The research establishes mathematical and control-theoretic methods to make generative AI safe, coordinated, and reliable for autonomous and networked systems...
- Federal Grant Award Summary The National Science Foundation (NSF) Computer and Information Science and Engineering program (CFDA 47.070) awarded $249,987 to the University of California, Berkeley on July 1, 2025, to conduct collaborative research on building a mathematical foundation for deep reinforcement learning (DRL). This project addresses a critical gap in theoretical understanding of DRL systems, which have achieved significant real-world breakthroughs in robotics, gaming, healthcare, and...
- The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded The University of Central Florida Board of Trustees $300,461 on October 1, 2026, through the Engineering program (CFDA 47.041) to develop theoretical foundations for long-term reinforcement learning under uncertainty. The project advances foundational artificial intelligence research by developing decision-making algorithms that optimize for steady-state, long-term performance in autonomous...
- The National Science Foundation Division of Computing and Communication Foundations awarded the University of California Irvine $548,422 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop approximate Bayesian inference methods for diffusion posteriors. The research creates posterior sampling methods that integrate pretrained diffusion models with observed data, making generative artificial intelligence systems more reliable for...
- The National Science Foundation Division of Computing and Communication Foundations awarded Massachusetts Institute of Technology $500,000 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) for collaborative research on reinforcement learning methods for imperfect-information games. The project develops theoretically sound, scalable policy-gradient algorithms and decision-time planning methods that enable deep reinforcement learning to operate...
- This $400,000 Project Grant awarded by the National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems under CFDA No. 47.041 Engineering aims to revolutionize the design of learning-enabled, safety-critical systems with a focus on power systems. The project at the University of California, Berkeley will introduce the concept of "antifragility" to promote system enhancement through change and uncertainty, rather than perceiving them as detriments. Key...
- The National Science Foundation Division of Computing and Communication Foundations awarded $364,815 to the Regents of the University of California, doing business as University of California, Berkeley, on April 15, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to establish rigorous theoretical and algorithmic frameworks for nonconvex and nonsmooth optimization problems. The research focuses on efficient computation of local solutions and effective...
The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded the University of California, Berkeley $150,000 on September 1, 2026, under the Engineering program (CFDA 47.041) to develop mathematical foundations for reinforcement learning and generative artificial intelligence systems. The project will establish stochastic analysis, stochastic control, and optimization theory for three interconnected research directions: continuous-time reinforcement learning in continuous state-action spaces with adaptive exploration and exploitation methods, policy optimization, and transfer learning for controlled diffusion processes; stochastic foundations for diffusion-based generative models; and algorithmic applications addressing uncertainty and time-dependent decision-making in evolving environments. The work targets reliability, efficiency, and controllability of AI systems operating under physical, economic, or scientific constraints, with applications across healthcare, transportation, energy systems, finance, and scientific computing. Performance occurs at Berkeley, California. The period of performance runs through August 31, 2029.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $150.0k | 8/10/26 |