CAREER: Energy-Efficient and Compact Foundation Model for Universal Virtual Sensing in Dyn — NSF Award to University of Illinois a
This NSF CAREER project aims to develop a new class of energy-efficient artificial intelligence (AI) models that can infer the internal behavior of complex energy systems from limited sensor measurements. Many critical infrastructures, including power grids and thermal energy systems, contain regions that cannot be dir
| Award title | CAREER: Energy-Efficient and Compact Foundation Model for Universal Virtual Sensing in Dyn |
|---|---|
| Award ID | 2543177 |
| Awardee | University of Illinois at Urbana-Champaign |
| City | URBANA |
| State | IL |
| Amount obligated | $587,981 |
| Principal investigator | Syed Bahauddin Alam |
| Program | EPCL: Energy, Power, Control, |
| Start date | 08/15/2026 |
| Abstract | This NSF CAREER project aims to develop a new class of energy-efficient artificial intelligence (AI) models that can infer the internal behavior of complex energy systems from limited sensor measurements. Many critical infrastructures, including power grids and thermal energy systems, contain regions that cannot be directly instrumented, yet safe and reliable operation requires knowledge of internal conditions such as temperature, voltage, and power balance. Existing AI methods are often computa |
| Source | NSF Awards |
$799/mo
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