Sham Kakade
Microsoft research - New England

I am a principal research scientist at Microsoft Research, New England, a lab in Cambridge, MA. Previously, I was an associate professor at the Department of Statistics, Wharton, University of Pennsylvania (from 2010-2012), and I was an assistant professor at the Toyota Technological Institute at Chicago. Before this, I did a postdoc in the Computer and Information Science department at the University of Pennsylvania under the supervision of Michael Kearns. I completed my PhD at the Gatsby Unit where my advisor was Peter Dayan. Before Gatsby, I was an undergraduate at Caltech where I did my BS in physics.

The focus of my work is on designing scalable and efficient algorithms for machine learning and artificial intelligence.
I have worked on problems in unsupervised (and representational) learning, algorithmic statistics, probabilistic inference, reinforcement learning, statistical learning theory, game theory, and economics. As a graduate student, I focused on reinforcement learning and computational neuroscience. My thesis was on sample complexity issues in reinforcement learning.


Publications at the Joint Centre: