This $350,000 National Science Foundation project grant supports statistical research at New York University from July 2022 through June 2025 under the Mathematical and Physical Sciences program (CFDA 47.049). The research aims to define a new measure of distance between distributions, called the Sketched Wasserstein Distance, that can be used to analyze high-dimensional datasets arising in fields like linguistics, computational biology, and particle physics. Key products will include...
This National Science Foundation Project Grant award of $540,000 provides funding from July 1, 2022 to June 30, 2025 to address new challenges in statistical inference with regularized optimal transport. The award is made under the Mathematical and Physical Sciences program (CFDA 47.049) to Cornell University to explore modern regularization techniques for optimal transport distances and develop a comprehensive statistical theory to facilitate principled inference in high dimensions....
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $600,000 Project Grant to Carnegie Mellon University (CMU) under the Mathematical and Physical Sciences program (CFDA 47.049). The grant supports a 3-year research project focused on developing rigorous statistical methods for Optimal Transport, a mathematical technique used to combine data from different scientific domains and mitigate unintended biases in algorithms. The project has three main thrusts: 1)...
This three-year, $631,860 project grant from the National Science Foundation's Division of Computing and Communication Foundations, under the Computer and Information Science and Engineering program, will support the development of efficient algorithms for optimal transport in geometric settings. The researchers at Duke University will advance theoretical understanding of optimal transport and bridge gaps between theory and practice of algorithm development. They will exploit combinatorial,...
This National Science Foundation Project Grant of $229,021 awarded on August 1, 2022 will support research at the University of Texas at Austin to develop mathematical frameworks in optimal transport applications to probability, machine learning, and kinetic theory through July 31, 2025. Under the Mathematical and Physical Sciences program (CFDA 47.049), the investigator will advance understanding of stochastic modeling, artificial intelligence algorithms, and kinetic theory by exploiting...
The National Science Foundation awarded a $239,999 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to the Georgia Tech Research Corporation from September 15, 2022 to August 31, 2025. The grant funds research to develop mathematical theories and efficient algorithms for multi-marginal optimal transport problems with graphical costs. Specifically, the principal investigator will establish a unified framework for these problems by merging concepts from optimal...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $184,593 project grant to Lafayette College in Easton, Pennsylvania. The grant, under the NSF's Mathematical and Physical Sciences program (CFDA 47.049), will fund collaborative research to develop theoretical tools and efficient numerical methods for solving the optimal transport problem. This mathematical problem seeks to minimize the total cost of transporting mass from one location to another, with applications...
This $228,693 Project Grant awarded by the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) supports collaborative research at Michigan State University to develop theoretical tools and efficient numerical methods for solving the optimal transport problem. The research aims to establish existence and characterize long-term behavior of solutions for a class of degenerate-parabolic fully nonlinear partial...
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 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) provides $113,834 to North Carolina State University to advance the theoretical foundations and develop efficient algorithms for optimal transport computations in geometric settings. The project aims to bridge the gap between the theory and practice of optimal transport algorithms, with a focus on designing scalable combinatorial algorithms that perform well on...