Collaborative Research: MFAI: Two Sides of a Tapestry: Causal Inference and Model Discover — NSF Award to Emory University (GA, $3
This project aims to advance machine learning methods for discovering cause-and-effect relationships in complex systems. While much of modern data science focuses on identifying patterns and correlations in data, such associations cannot explain why events happen or how changing one factor might influence another. Caus
| Award title | Collaborative Research: MFAI: Two Sides of a Tapestry: Causal Inference and Model Discover |
|---|---|
| Award ID | 2502299 |
| Awardee | Emory University |
| City | ATLANTA |
| State | GA |
| Amount obligated | $340,000 |
| Principal investigator | Razieh Nabi |
| Program | APPLIED MATHEMATICS, EPCL: Energy, Power, Control, |
| Start date | 10/01/2025 |
| Abstract | This project aims to advance machine learning methods for discovering cause-and-effect relationships in complex systems. While much of modern data science focuses on identifying patterns and correlations in data, such associations cannot explain why events happen or how changing one factor might influence another. Causal discovery addresses this fundamental challenge by revealing the mechanisms behind observed phenomena, enabling more informed decisions, reliable predictions, and targeted interv |
| Source | NSF Awards |
$799/mo
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