This Project Grant award, valued at $370,000.00, was provided by the National Science Foundation (NSF) through its Mathematical and Physical Sciences (CFDA 47.049) program. The grant supports fundamental and applied research to advance the understanding of random matrices, which have significant applications across physics, data science, and mathematics. The key objectives of this award are to: (1) develop new probabilistic techniques for the analysis of random matrix models and their...
The National Science Foundation (NSF) awarded a $146,350 Project Grant to The Trustees of the University of Pennsylvania (Penn) under the Mathematical and Physical Sciences program (CFDA 47.049) on July 1, 2023. The grant funding supports research aimed at broadening the understanding of the universality phenomenon of random matrices and developing new tools and techniques for additional applications of random matrix theory. Specifically, the project will explore two research directions: 1)...
The National Science Foundation awarded a $260,737 Project Grant to the University of Colorado Boulder under the Mathematical and Physical Sciences program (CFDA 47.049). The grant funds the CAREER: BEYOND INDEPENDENCE: RANDOM MATRICES AND APPLICATIONS project from July 1, 2022 through June 30, 2027. The project aims to advance understanding of random matrix theory and its applications through research and education activities. As part of the Mathematical and Physical Sciences program's goal...
The National Science Foundation (NSF) awarded a three-year, $150,000 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) federal grant program to the Regents of the University of Minnesota. The grant aims to develop new statistical methods for inference with high-dimensional dependent data, such as that generated by single-cell and spatially-resolved sequencing technologies. Specifically, the project will address challenges in statistical inference near the boundary of the...
The National Science Foundation (NSF) awarded a $160,000 Project Grant through its Mathematical and Physical Sciences (CFDA 47.049) program to the Regents of the University of Minnesota to support research on the mathematical modeling of "moiré materials" - novel 2D materials formed by stacking 2D layers with a relative twist. The project aims to develop advanced mathematical methods for predicting the emergent strongly correlated electronic phases in these materials, which hold...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $250,000 Project Grant to Yale University from September 1, 2023 to August 31, 2026 under the Mathematical and Physical Sciences program (CFDA 47.049). The grant supports the development of a new perturbation theory to improve statistical analysis of large data matrices, particularly those with low-rank structure and random noise. Key anticipated outcomes include optimal error bounds for matrix parameters like...
This three-year, $260,000 project grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) supports research at Duke University on large deviations and extremes for random matrices, tensors, and fields. The grant aims to advance understanding of rare events and extreme values through analysis of nonlinear functions of random hypergraphs and matrices, with a focus on applications to social networks and reaction-diffusion systems modeling invasive...
The National Science Foundation Division of Mathematical Sciences awarded $285,000 under the Mathematical and Physical Sciences federal grant program (CFDA 47.049) to the Regents of the University of Minnesota for a project grant titled "Critical Phenomena in Coherent Structure Formation." The grant supports research from July 15, 2022 to June 30, 2025 to develop new analytical and computational tools to systematically analyze, predict, and validate models of self-organized coherent...
This Project Grant from the National Science Foundation Division of Mathematical Sciences will fund the development of robust algorithms for analyzing corrupted data. Totaling $207,194, the award will support research from September 1, 2023 through August 31, 2028 under the Mathematical and Physical Sciences program. The grantee, Regents of the University of Minnesota, will design efficient algorithms using two methodologies. First, algorithms will assume underlying low-rank data structures...
This National Science Foundation (NSF) Project Grant award of $210,000.00, under the Mathematical and Physical Sciences (CFDA 47.049) program, supports research at the University of Minnesota on generalized determinantal varieties. The project examines symplectic matrix Schubert varieties, alternating sign matrix varieties, and quiver loci through the development of diagonal Gröbner geometry theory. Key goals include providing opportunities for undergraduate, graduate, and postdoctoral...