June 5, 11:15am
Location: Santa Clara II

AI for Earth Sciences on Supercomputers

AI is driving new insights in fundamental sciences. The field is on the verge of having a transformative impact, and doing so will not only require novel deep learning approaches, but also exploiting large-scale computing resources. This talk will highlight some particular recent applications of deep learning for earth sciences, as well as related fundamental science fields, and explain how these applications are exploiting supercomputers, such as those at NERSC, Berkeley Lab, to achieve novel insights. We will also offer some perspectives on what challenges remain to be tackled and what future directions will be needed for AI to achieve its potential for science.

Peter Harrington is a machine learning engineer in the Data and Analytics Services group at the National Energy Research Scientific Computing Center (NERSC). There, he works with domain scientists on deep learning applications in a variety of scientific fields. He also helps maintain and benchmark the deep learning software stack on NERSC’s supercomputers, assists users with their AI workflows, and engages the scientific ML community with training events. He has a background in physics and computing, with a BS in Astrophysics and a MS in Scientific Computing & Applied Mathematics from the University of California Santa Cruz. Previously, Peter worked at Berkeley Lab as an applied machine learning researcher in the Computational Research Department.