Pritish Kamath is a postdoc at Toyota Technological Institute at Chicago. His current research interests include various aspects of theoretical machine learning, including reinforcement learning and generalization theory. He obtained a PhD from MIT, where his research focused on various aspects of theoretical computer science, in particular, on understanding the computational hardness in problems across different domains such as algebraic complexity and communication complexity.
He has been a research fellow at the Simons Institute in the program on "Foundations of Deep Learning", an intern at Google DeepMind, and a Research Fellow at Microsoft Research India. He completed a BTech in computer science and engineering at IIT Bombay.