Project Grant FA8655261B023

This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program provides $600,000 to the University of Michigan to develop a new analytical method for analyzing large-scale stochastic systems from July 2022 to June 2025. The method aims to obtain non-asymptotic performance bounds for stochastic networks and systems using Lyapunov drift analysis combined with ideas from Stein's method, dimensionality reduction, and reproducing kernel Hilbert...

This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award, titled "New Frontiers in Expansion", provides $600,000 in funding to the University of California, Berkeley (UC Berkeley) from August 1, 2024 through July 31, 2027. The project aims to address two key mysteries regarding network expansion: 1) the optimal tradeoff between network sparsity and mixing rate, which is critical for the performance of...

The National Science Foundation awarded a $466,463 Project Grant to the University of California Irvine under the Mathematical and Physical Sciences program (CFDA 47.049). The grant supports research into non-stationary random dynamical systems and their applications from June 2023 through May 2026. Key areas of focus include proving that smooth random dynamical systems under an assumption of absence of invariant measures must lead to almost sure exponential growth of norms of random...

This project grant, awarded by the National Science Foundation's Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049), provides $200,000 in funding to the University of Utah for a two-year period (July 1, 2025 – June 30, 2027). The award supports fundamental mathematical research focused on understanding random growth patterns and stochastic processes that occur naturally in complex systems such as disease spread, crystal formation, and traffic...

This three-year Project Grant from the National Science Foundation's Mathematical and Physical Sciences program, totaling $259,999, will support research into dynamical evolutions in complex, high-dimensional energy landscapes. Specifically, the awardee, Northwestern University, will investigate Markov chain dynamics arising from spin systems in statistical physics, which serve as prototypical examples for protein folding, evolutionary dynamics, out-of-equilibrium thermodynamics, and neural...

The National Science Foundation (NSF) Division of Mathematical Sciences has awarded a $300,000 Project Grant to Cornell University to support research on stochastic models and their properties. The key objectives of this 3-year grant, which runs from July 15, 2023 to June 30, 2026, are to: Develop novel methodologies to characterize different types of orbits exhibited by Markov semigroups on Hilbert spaces, providing a comprehensive understanding of these structures. Utilize the classification...

This $330,000 National Science Foundation Project Grant through the Mathematical and Physical Sciences program (CFDA 47.049) supports research at Stanford University on mathematical foundations for Yang-Mills theory, randomly growing surfaces, and related systems. The project aims to advance understanding of Yang-Mills theories, which underpin particle physics, by constructing solutions to the Yang-Mills heat equation with random initial data for the first time. It will also study convergence to...

This Project Grant award of $186,772 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, with a period of performance from January 1, 2025 to October 31, 2025, supports a collaborative research project between Rutgers, The State University to develop a data-driven, systemic model of hippocampal spatial learning. The research aims to link the parameters of synaptic connectivity and plasticity in the hippocampus to the cognitive dynamics of...

The National Science Foundation awarded Florida State University a $163,533 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) from July 1, 2022 to June 30, 2025. The award will support research developing a theoretical framework to better understand how heavy-tailed distributions arise in popular machine learning algorithms and how they can explain the success of these algorithms. The awardee will conduct research obtaining theoretical convergence properties,...

This Project Grant award from the National Science Foundation (NSF) Mathematical and Physical Sciences (MPS) program in the amount of $199,555 supports collaborative research on stochastic shape processes and inference. Led by a team of investigators from the U.S. and U.K., the project will develop methods for modeling how biological and other shapes change over time, using statistical frameworks to capture shape variations across objects and populations. This research aims to advance the...