Collaborative Research: Statistical Foundations for Scalable and Robust Data Valuation — NSF Award to Carnegie Mellon University (
High-quality data are increasingly central to modern machine learning and artificial intelligence, enabling advances in scientific discovery, automated decision-making, and emerging AI technologies. Yet there often lack transparent and reliable mechanisms to appropriately credit and compensate those who contribute data
| Award title | Collaborative Research: Statistical Foundations for Scalable and Robust Data Valuation |
|---|---|
| Award ID | 2610423 |
| Awardee | Carnegie Mellon University |
| City | PITTSBURGH |
| State | PA |
| Amount obligated | $150,000 |
| Principal investigator | Weijing Tang |
| Program | STATISTICS |
| Start date | 07/01/2026 |
| Abstract | High-quality data are increasingly central to modern machine learning and artificial intelligence, enabling advances in scientific discovery, automated decision-making, and emerging AI technologies. Yet there often lack transparent and reliable mechanisms to appropriately credit and compensate those who contribute data used to train AI systems. This project will develop statistical and machine-learning methods for measuring the value of data in AI model training and data-driven decision systems. |
| Source | NSF Awards |
$799/mo
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