CAREER: Theoretically Guaranteed Structure-Informed Machine Learning and Data-Driven Struc — NSF Award to Georgia Tech Research Co
Machine learning is rapidly changing science, engineering, and technology, but many of its most successful methods require enormous amounts of high-quality data. This limits their usefulness in scientific settings where data may be expensive, noisy, incomplete, or difficult to obtain, such as turbulence modeling, molec
| Award title | CAREER: Theoretically Guaranteed Structure-Informed Machine Learning and Data-Driven Struc |
|---|---|
| Award ID | 2540370 |
| Awardee | Georgia Tech Research Corporation |
| City | ATLANTA |
| State | GA |
| Amount obligated | $246,901 |
| Principal investigator | Wei Zhu |
| Program | COMPUTATIONAL MATHEMATICS |
| Start date | 06/01/2026 |
| Abstract | Machine learning is rapidly changing science, engineering, and technology, but many of its most successful methods require enormous amounts of high-quality data. This limits their usefulness in scientific settings where data may be expensive, noisy, incomplete, or difficult to obtain, such as turbulence modeling, molecular design, medical imaging, and the study of complex physical systems. This project will develop new mathematical foundations and computational tools that allow machine learning |
| Source | NSF Awards |
$799/mo
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