Sham Kakade

Sham Machandranath Kakade is an American computer scientist. He is a Gordon McKay Professor in Computer Science at Harvard University, with a joint appointment in the Department of Statistics. Kakade is a co-director of the Kempner Institute for the Study of Natural and Artificial Intelligence. He co-founded the Algorithmic Foundations of Data Science Institute.

Education and Career Kakade earned a Bachelor of Science in Physics from the California Institute of Technology and a PhD from the Gatsby Computational Neuroscience Unit at University College London, under the supervision of Peter Dayan. Kakade has contributed to theoretical analyses of reinforcement learning algorithms with provable performance guarantees. He co-authored "Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design," which studied Gaussian process methods in a nonparametric bandit setting. The work established regret bounds connected to information gain in Gaussian process models. The ICML awards committee cited the paper's influential role in connecting Gaussian process models, bandit optimization, and experimental design. Kakade has served on the Alfred P. Sloan Foundation's selection committee for the Computer Science Sloan Research Fellowships.