The National Science Foundation (NSF) awarded a $689,835 Project Grant titled "AIMING: DISCOVERY THROUGH MACHINE LEARNING IN PARTIAL DIFFERENTIAL EQUATIONS" to Brown University. This 3-year grant, starting on December 1, 2024, aims to develop machine learning approaches for solving longstanding open problems in nonlinear partial differential equations, including dispersive, elliptic, and geometric frameworks. The project also intends to advance the heuristics behind machine learning numerics for such equations, guided by new mathematical knowledge. Key research tasks include investigating the incompressible Euler equation, addressing elliptic partial differential equations, studying geometric partial differential equations and Calabi-Yau metrics, and developing MathLib and Lean code. The grant supports the training of undergraduates, graduate students, and postdocs, and involves efforts to enhance and broaden participation in the mathematical community through conferences, new courses, and open-source code contributions.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $689.8k | 8/20/24 |