Project Grant 2443097

Award Date 6/1/25
Completion Date 5/31/30
Dollars Obligated $118K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Hamden, CT 06511, USA
Similar Awards
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) grant award (CFDA 47.070) for $108,647 will fund a 4-year collaborative research project led by Yale University exploring a novel algorithmic framework called the "LCP Scheme" which leverages Hamiltonian dynamics to address challenges in optimization, random sampling, and game theory for modern AI and machine learning systems. The project aims to develop a systematic methodology that utilizes...
This federal Project Grant award, provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program, will support research at New York University (NYU) to advance the theory of dynamical systems and investigate its applications in fields such as engineering and the biological sciences. The $375,506 award, effective from July 1, 2024 to June 30, 2029, will fund four primary research projects: Extending finite-dimensional dynamical systems...
This Project Grant award of $600,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support research at the Massachusetts Institute of Technology (MIT) from October 1, 2024 to September 30, 2027. The project aims to design better algorithms for learning problems in linear dynamical systems, graphical models, and hidden Markov models, with the goal of bridging the gap between the tools and perspectives of classic...
This Project Grant award from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) provides $100,000 to the University of California, San Diego (UCSD) for a 4-year research project on developing a new algorithmic theory for optimization, sampling, and game theory in modern AI and machine learning systems. The project aims to leverage Hamiltonian dynamics, a fundamental concept in physics and mathematics, to create a systematic methodology called the...
This National Science Foundation (NSF) Project Grant award under the Mathematical and Physical Sciences (CFDA 47.049) program seeks to advance the understanding of dynamical systems and the evolution from ordered to chaotic behavior. The $249,103 award to the Research Foundation of the City University of New York, effective July 1, 2024 through June 30, 2026, will support research aimed at developing new conceptual ideas, approaches, and theoretical frameworks to transcend the limitations of...
This $166,285 federal Project Grant award from the National Science Foundation's (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences (CFDA 47.049) program supports the development of new mathematical approaches and tools for analyzing complex nonlinear dynamics and bifurcations in high-dimensional systems. The goal is to enable quantitative and qualitative progress in studying data-driven, detailed, and phenomenologically-reduced models with complex nonlinear...
This $599,744 federal Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program supports research by Yale University to develop new theory and methods for analyzing, training, and designing complex, high-dimensional multi-agent games and machine learning systems. The key activities under this 3-year award include: Developing optimal uncoupled algorithms for computing and learning equilibria in high-dimensional concave games...
This $287,367 National Science Foundation award under the Computer and Information Science and Engineering program will support research and education activities at the University of Michigan from September 2023 through August 2028. The goal of the project is to advance the theory of dynamic graph algorithms through multi-disciplinary connections to areas like differential privacy, cryptography, and optimization methods. Specific aims include developing techniques for dynamic algorithms robust...
This $199,996 project grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) aims to develop a principled approach to the systematic design of efficient iterative algorithms for a wide variety of data-driven applications. The project at Miami University will leverage tools from both optimization and control theory, including techniques like interpolation, Lyapunov stability, and robust control synthesis, to enable the deployment of specialized and efficient...
The National Science Foundation (NSF) awarded a $369,218 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to the University of California, San Diego (UCSD) to develop analytical methods for approximating the state of certain dynamical systems. The project aims to advance the understanding of quantitative aspects of the analysis of dynamical systems, with a focus on rigidity phenomena in the dynamics of group actions on structured spaces. Key research areas include...

This $117,843 federal Project Grant award from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will support research at Yale University aimed at developing a rigorous, general theory for translating continuous-time dynamical systems into discrete-time algorithms. The goal is to create a systematic approach for deriving algorithms from dynamical systems models that can preserve key properties like convergence guarantees, with a focus on optimization and sampling problems relevant to machine learning applications. The work will involve combining ideas from dynamical systems, geometry, probability, and information theory to derive new algorithmic principles and design practical algorithms. This 5-year project will also provide training opportunities for students and outreach to popularize the dynamical systems perspective on algorithm design.

Generated 4/29/25, 3:51 AM