CAREER: Trustworthy Learning-Enabled Autonomy: Safe, Robust, and Scalable Data-Driven Deci — NSF Award to Massachusetts Institute
This NSF CAREER project aims to develop foundations that allow autonomous systems to learn from data while reliably respecting safety constraints. AI-enabled vehicles, robots, and infrastructure controllers are moving into public spaces and critical services, where rare mistakes can cause injuries or cascading disrupti
| Award title | CAREER: Trustworthy Learning-Enabled Autonomy: Safe, Robust, and Scalable Data-Driven Deci |
|---|---|
| Award ID | 2544396 |
| Awardee | Massachusetts Institute of Technology |
| City | CAMBRIDGE |
| State | MA |
| Amount obligated | $659,678 |
| Principal investigator | Navid Azizan Ruhi |
| Program | EPCL: Energy, Power, Control, |
| Start date | 04/01/2026 |
| Abstract | This NSF CAREER project aims to develop foundations that allow autonomous systems to learn from data while reliably respecting safety constraints. AI-enabled vehicles, robots, and infrastructure controllers are moving into public spaces and critical services, where rare mistakes can cause injuries or cascading disruptions. Many modern learning components provide limited guarantees: they may violate constraints, fail when conditions differ from training data, or scale poorly when many decision ma |
| Source | NSF Awards |
$799/mo
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