Scholar
Ashesh Chattopadhyay
Google Scholar ID: wtHkCRIAAAAJ
University of California, Santa Cruz
Citations & Impact
Citations
3,357
H-index
19
i10-index
24
Publications
20
Co-authors
20
list available
Contact
No contact links provided.
Publications
Resume (English only)
Academic Achievements
- The work is generously funded by the National Science Foundation, Defense Advanced Research Projects Agency, and the National Research Foundation in Korea, with close collaboration with industries in Silicon Valley.
Research Experience
- Leads or participates in research that involves using deep learning models to predict the inherent limits of multi-scale flows, data assimilation with SciML, understanding biases and failure modes in SciML, among other topics.
Background
- Focused on the theoretical and applied aspects of complex systems, including deep learning theory, scientific machine learning (SciML), and their applications in nonlinear dynamical systems, particularly in atmospheric, oceanic, and engineering turbulence.
Miscellany
- Interested in several intriguing questions at the intersection of physics and deep learning; also focuses on random matrix theory and its implications for understanding SciML; dedicated to high-performance computing, reduced-order modeling, etc., for large-scale systems.
