CAREER: Robust Learning via Optimal Transport — NSF Award to Cornell University (NY, $670,000)
This NSF CAREER project aims to develop the mathematical tools required to build robust Artificial Intelligence (AI) systems that remain reliable in unpredictable, real-world conditions. While current AI models are highly effective in controlled settings, they can be fragile when faced with unexpected data shifts or ad
| Award title | CAREER: Robust Learning via Optimal Transport |
|---|---|
| Award ID | 2541066 |
| Awardee | Cornell University |
| City | ITHACA |
| State | NY |
| Amount obligated | $670,000 |
| Principal investigator | Soroosh Shafiee |
| Program | EPCL: Energy, Power, Control, |
| Start date | 04/01/2026 |
| Abstract | This NSF CAREER project aims to develop the mathematical tools required to build robust Artificial Intelligence (AI) systems that remain reliable in unpredictable, real-world conditions. While current AI models are highly effective in controlled settings, they can be fragile when faced with unexpected data shifts or adversarial attacks where data is geometrically manipulated to cause errors. The project will advance the state-of-the-arts by shifting from defensive methods that only patch specifi |
| Source | NSF Awards |
$799/mo
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