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Karthik Kashinath's research spans the areas of fluid dynamics, nonlinear dynamics and climate dynamics. Karthik uses and develops methods from artificial intelligence, machine learning, deep learning, applied topology, dynamical systems theory and complexity theory to discover patterns in physical systems, emulate complex physical processes and build predictive spatio-temporal models. He also investigates ways to incorporate prior knowledge about the physics and dynamics of such systems into AI models. An overarching research focus area is improving our understanding of extreme weather and climate events and how they are changing under global warming.

Karthik Kashinath received his Bachelors from the Indian Institute of Technology, Madras in 2007, Masters from Stanford University in 2009, and PhD from the University of Cambridge, U. K. in 2013. His educational background is in engineering and physics. Since 2013 he has been a part of Lawrence Berkeley National Laboratory working as a climate scientist and AI specialist.
Machine Learning, Deep Learning and Artificial Intelligence
Parallel Programming Languages, Libraries, and Models
Best Student Paper Finalist
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