Project Grant 2246611
- 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 $113,834 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports collaborative research at North Carolina State University to develop efficient algorithms for optimal transport in geometric settings. The project aims to advance the theoretical underpinnings of optimal transport, a powerful tool for comparing probability distributions, and bridge the gap between theory and practice of algorithms. By...
- This National Science Foundation Project Grant of $315,519 supports research at the University of California, Los Angeles from July 2022 to June 2025 under the Mathematical and Physical Sciences program (CFDA 47.049). The award funds research investigating challenging problems in optimal transport theory and its applications in fields including partial differential equations, geometry, probability, and machine learning. Key areas of focus include developing the theory to analyze games with large...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will provide $160,000 to Cornell University from July 1, 2024 to June 30, 2027 to advance statistical optimal transport theory and its applications. The research project aims to develop new computational and statistical methods for optimal transport, and apply them to various data analysis tasks like clustering, generative modeling, and dimension reduction for...
- This federal Project Grant award of $257,986 from the National Science Foundation (NSF) Division of Mathematical Sciences (CFDA 47.049 - Mathematical and Physical Sciences) is funding research by Texas A&M University to study transportation cost spaces, also known as Lipschitz-free spaces, Wasserstein spaces, Arens-Eals spaces, and Earthmover spaces. The research aims to obtain a deeper understanding of the structure of these mathematical spaces and develop improved techniques for...
- Federal Project Grant Award Summary Georgia TECH Research Corp received a $204,069 Project Grant from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049), awarded July 15, 2025, with completion targeted for June 30, 2028. The award supports fundamental research on optimal transport theory, regularity analysis, and branched microstructures—mathematical frameworks applicable to resource allocation, quantum...
- This $300,000 federal Project Grant, awarded by the National Science Foundation (NSF) Division of Mathematical Sciences on June 1, 2024, supports fundamental research across two key areas: billiard models and geometrical optics, and vehicle kinematics and tire track geometry. The project aims to address challenges in ray optics, mathematical billiards, and vehicle motion modeling, with potential applications in areas like light trapping, invisibility, laser beam shaping, tractor control,...
- Project Grant Award Summary: Optimal Transport for Risk Management and Scenario Generation New York University received a $299,057 Project Grant from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) for the period September 1, 2025 through August 31, 2027. The OTRIMAGE (Optimal Transport for Risk Management and Scenario Generation) project delivers fundamental mathematical research and methodological...
- 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,...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $400,000 Project Grant to New York University (NYU) for the period of August 1, 2023 to July 31, 2026. The grant, funded under the Mathematical and Physical Sciences program (CFDA 47.049), focuses on two key areas: Studying geometric evolution equations, specifically mean curvature flow and Ricci flow, with a focus on different aspects of regularity. This research aims to address longstanding open problems at the...
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 in areas such as lens design, atmospheric modeling, and economic assignment problems. The project will focus on establishing the existence and characterizing the long-term behavior of solutions to a class of degenerate-parabolic, fully nonlinear partial differential equations related to the Monge-Ampère equation. This theoretical work aims to provide a foundation for developing robust numerical algorithms that can be mathematically guaranteed to exhibit outstanding performance in solving optimal transport problems.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $184.6k | 7/10/23 |