Project Grant 2544658
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Computing and Communication Foundations awarded a four-year, $364,815 Project Grant to The Regents of the University of California, doing business as University of California, Berkeley, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The award, initiated April 15, 2026 and concluding March 31, 2031, supports fundamental research and algorithmic development in nonconvex nonsmooth...
- Federal Grant Award Summary Georgia Tech Research Corporation received a $661,515 Project Grant award from the National Science Foundation's Division of Computing and Communication Foundations under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective October 1, 2025, through September 30, 2029. This collaborative research initiative delivers fundamental algorithmic research and complexity analysis focused on optimization techniques applicable to...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems awarded $200,000 to the University of Massachusetts on June 15, 2025, under the Engineering program (CFDA 47.041) for a project titled "Closed-Loop Hybrid Intelligence with Optogenetic-Neuromorphic Co-Designed Cell Interfaces." The project, scheduled for completion by May 31, 2028, delivers advanced engineering tools and methods that integrate high-resolution...
- 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...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Computing and Communication Foundations awarded $375,000 to UCLA under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) on August 15, 2025, for a collaborative research project extending through July 31, 2028. This project grant supports the development of specialized theoretical frameworks and algorithms for min-max optimization, a mathematical approach that underpins critical...
- Federal Grant Award Summary This $174,999 Project Grant award, issued September 1, 2025, by the National Science Foundation's Division of Computing and Communication Foundations under the Computer and Information Science and Engineering program (CFDA 47.070), supports a unified Large Language Model (LLM)-empowered framework for systematic software performance issue testing, localization, and optimization at California State University Long Beach Research Foundation. The project will deliver...
- Federal Grant Award Summary The National Science Foundation's Division of Computing and Communication Foundations awarded The Johns Hopkins University $525,000 under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) for a collaborative research project spanning August 15, 2025 through July 31, 2028. This project grant supports fundamental research in min-max optimization theory and algorithm development, addressing critical gaps in mathematical frameworks and...
- Federal Grant Award Summary The National Science Foundation (NSF) awarded The Leland Stanford Junior University a $677,600 Project Grant on September 15, 2025, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop advanced artificial intelligence (AI) systems capable of proving graduate-level mathematical theorems and tackling unsolved mathematical problems. The primary deliverable is the creation of an AI system trained using novel methodologies that replicate how...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Mathematical Sciences awarded $255,237 to the University of Minnesota under the Mathematical and Physical Sciences (CFDA 47.049) program for a collaborative research project running from September 1, 2025, through August 31, 2028. This project focuses on developing acceleration and preconditioning methods to optimize deep learning (artificial intelligence) model training processes. The research leverages numerical...
- Federal Grant Award Summary The National Science Foundation (NSF) Division of Computing and Communication Foundations awarded a $180,000 Project Grant to Trustees of Tufts College beginning October 1, 2025, and concluding September 30, 2027, under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This collaborative research initiative addresses intellectual property protection challenges arising from the use of generative artificial intelligence (AI) in...
This $349,963 Project Grant, awarded June 1, 2026, by the National Science Foundation's (NSF) Division of Computing and Communication Foundations under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports a five-year research initiative at Toyota Technological Institute at Chicago to develop optimization theory specifically tailored to deep learning architectures. The project delivers foundational research and theoretical frameworks that link optimization methods to neural network structures, addressing three complementary research directions: structured preconditioning, non-Euclidean descent methods adapted to different distance notions, and scale invariance induced by normalization layers. The research analyzes representative model components including multilayer perceptrons, attention modules, and embedding parameters to establish when architecture-matched optimization methods improve training efficiency and characterize their behavior on complex loss landscapes. Beyond core research deliverables, the award supports educational outcomes including graduate education in optimization for deep learning, research-preparation activities for undergraduate students, and hands-on artificial intelligence learning modules for local high school students with open participation. The project's scientific contributions aim to reduce computational costs and energy consumption in model training, provide evidence-based guidance for practitioners, and support the development of more efficient and reliable artificial intelligence systems, with anticipated benefits extending across industry and academic applications.Federal Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $350.0k | 5/13/26 |