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Prabhat leads the Data and Analytics Services team at NERSC; his group is responsible for supporting over 7000 scientific users on NERSC’s HPC systems. His current research interests include Deep Learning, Machine Learning, Applied Statistics and High Performance Computing. In the past, Prabhat has worked on topics in scientific data management; he co-edited a book on ‘High Performance Parallel I/O’.
Prabhat received a B.Tech in Computer Science and Engineering from IIT-Delhi (1999); ScM in Computer Science from Brown University (2001) and a PhD in Earth and Planetary Sciences from U.C. Berkeley (2020). Prabhat has co-authored over 150 papers spanning several domain sciences and topics in computer science. He has won 5 Best Paper Awards, 3 Industry Innovation Awards, and he was a part of the team that won the 2018 Gordon Bell Prize for their work on ‘Exascale Deep Learning’.
Machine Learning, Deep Learning and Artificial Intelligence
Parallel Programming Languages, Libraries, and Models
Best Student Paper Finalist
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