Collaborative Research: Scientific Computing Assisted Machine Learning for Wave Imaging — NSF Award to University of North Carolin
Computational wave imaging, vital for uncovering hidden properties in diverse fields of science and engineering, such as materials science, medicine, and geoscience, faces significant challenges. Traditional methods struggle with the inherent complexity and computational demands of such problems. Although deep learning
| Award title | Collaborative Research: Scientific Computing Assisted Machine Learning for Wave Imaging |
|---|---|
| Award ID | 2504439 |
| Awardee | University of North Carolina at Chapel Hill |
| City | CHAPEL HILL |
| State | NC |
| Amount obligated | $220,000 |
| Principal investigator | Youzuo Lin |
| Program | CDS&E-MSS, OFFICE OF MULTIDISCIPLINARY AC, COMPUTATIONAL MATHEMATICS |
| Start date | 09/01/2025 |
| Abstract | Computational wave imaging, vital for uncovering hidden properties in diverse fields of science and engineering, such as materials science, medicine, and geoscience, faces significant challenges. Traditional methods struggle with the inherent complexity and computational demands of such problems. Although deep learning offers promise for these scientific inverse problems, its efficacy is hindered by the scarcity of labeled data, often due to costly experiments and expertise requirements. This un |
| Source | NSF Awards |
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