Multiscale random matrices, inference and learning in high dimensions — NSF Award to Tulane University (LA, $199,626)
In several areas of scientific investigation, such as genomics, astrophysics, and network traffic, traditional modeling tools are inadequate for handling the vast amounts of data generated by modern technology. This project will bring together a team of collaborators to tackle the challenge of developing new methodolog
| Award title | Multiscale random matrices, inference and learning in high dimensions |
|---|---|
| Award ID | 2515732 |
| Awardee | Tulane University |
| City | NEW ORLEANS |
| State | LA |
| Amount obligated | $199,626 |
| Principal investigator | Gustavo Didier |
| Program | STATISTICS, OFFICE OF MULTIDISCIPLINARY AC |
| Start date | 08/01/2025 |
| Abstract | In several areas of scientific investigation, such as genomics, astrophysics, and network traffic, traditional modeling tools are inadequate for handling the vast amounts of data generated by modern technology. This project will bring together a team of collaborators to tackle the challenge of developing new methodologies for analyzing complex and multiscale data. The group is both multidisciplinary (mathematics, statistics, and signal processing) and international (U.S. and France). The driving |
| Source | NSF Awards |
$799/mo
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