Collaborative Research: CAIG: Next Generation Machine-Learning Approach to Decode High-Res — NSF Award to Carnegie Mellon Universi
Understanding and predicting earthquakes is a critical endeavor that has profound implications for public safety and disaster preparedness. By developing cutting-edge machine learning models and algorithms, this project seeks to uncover the intricate dynamics of earthquakes, potentially identifying precursory signals t
| Award title | Collaborative Research: CAIG: Next Generation Machine-Learning Approach to Decode High-Res |
|---|---|
| Award ID | 2425888 |
| Awardee | Carnegie Mellon University |
| City | PITTSBURGH |
| State | PA |
| Amount obligated | $392,914 |
| Principal investigator | Shixiang Zhu |
| Program | GEO CI - GEO Cyberinfrastrctre |
| Start date | 10/01/2024 |
| Abstract | Understanding and predicting earthquakes is a critical endeavor that has profound implications for public safety and disaster preparedness. By developing cutting-edge machine learning models and algorithms, this project seeks to uncover the intricate dynamics of earthquakes, potentially identifying precursory signals that precede major seismic events. The broader impact of this work includes enhancing our ability to forecast earthquakes more accurately, thus mitigating risks and improving resili |
| Source | NSF Awards |
$799/mo
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