This $597,791 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support collaborative research at Duke University to explore the synergies between machine learning and partial differential equations (PDEs). The research aims to strengthen the use of machine learning methods, specifically neural networks, for improving PDE solving processes, as well as to further elucidate the role of PDEs in generative AI modeling. The investigators will leverage expertise in the mathematical foundations of PDEs and generative modeling, as well as numerical optimization, to advance the integration of these fields. The award, with a performance period from August 2024 through July 2028, reflects NSF's priorities in supporting transformative research at the intersection of computing, mathematics, and AI.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $597.8k | 8/15/24 |