Gregory Valiant

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I am an Associate Professor in Stanford's Computer Science Department, working on Algorithms, Machine Learning, Statistics, and Information Theory. One of the main themes in my work is the design of efficient algorithms for accurately inferring information about complex distributions, given limited amounts of data, or limits on other resources such as the computation time, available memory, communication, or the quality of the available data. Prior to joining Stanford, I was a postdoc at Microsoft Research, New England, and received my PhD from Berkeley in Computer Science, and BA in Math from Harvard.

My office is 162 Gates.

I am extremely lucky to advise the following PhD students:
Annie Marsden (coadvised with John Duchi), Steven Cao (coadvised with Percy Liang), Chirag Pabbaraju (coadvised with Moses Charikar), Spencer Compton (coadvised with Tselil Schramm), Aidan Perreault (coadvised with Moses Charikar)

Former PhD students:
Shivam Garg, PhD 2023 (postdoc at Harvard)
Jay Mardia (coadvised with Tsachy Weissman), PhD 2023
Mingda Qiao, PhD 2023 (Berkeley/MIT FODSI postdoc --> Asst. Prof at Umass)
Neha Gupta (coadvised with Moses Charikar), PhD 2022 (Research Scientist at Google)
Brian Axelrod (coadvised with Omer Reingold), PhD 2022 (Waymo)
Kai Sheng Tai (coadvised with Peter Bailis), PhD 2021 (Research Scientist at Facebook)
Vatsal Sharan, PhD 2020. (Assistant Prof at USC starting Fall, 2021.)
Weihao Kong , PhD 2019 (Research Scientist at Google)
Hongyang Zhang (coadvised with Ashish Goel), PhD 2019 (Assistant Prof at Northeastern starting Fall, 2020.)