Ankur Moitra's homepage


Rockwell International Career Development Associate Professor
David and Lucile Packard Foundation Fellow
Alfred P. Sloan Foundation Fellow
Department of Mathematics, Massachusetts Institute of Technology
Principal Investigator, Computer Science and Artificial Intelligence Laboratory


I am a theoretical computer scientist, and a major goal in my work is to give algorithms with provable guarantees for various problems in machine learning. See my publications and talks for more information. I am a member of the Theory of Computation group, MachineLearning@MIT, Foundations of Data Science and the Center for Statistics.


If you are interested in recent developments in algorithms for machine learning, check out these lecture notes, which will be published in a revised form with Cambridge University Press.


I co-organize the Theory of Computing Colloquium and the Harvard/MIT/MSR Reading Group.


I co-organized New Challenges in Machine Learning: Robustness and Nonconvexity at STOC 2017.
I co-taught Learning at Scale, a summer school at MADALGO in 2014.
I co-organized Overcoming Intractability in Unsupervised Learning at STOC 2014.
I co-organized Topic Models: Computation, Application, and Evaluation at NIPS 2013.


I am an Associate Editor for ACM Transactions on Algorithms. I am/will be on the Program Committee for COLT 2018, ICALP 2018, STOC 2018, RANDOM 2017, ICML 2016, SODA 2015, FOCS 2014, ICML 2013 and APPROX 2013.


My research is supported by a David and Lucile Packard Fellowship, an NSF Large (with Barak, Kelner, Parrilo) CCF-1565235, an NSF CAREER Award, an Alfred P. Sloan Fellowship and a Google Research Award.


Email: "lastname" at mit dot edu
Offices: 2-472 (default) and 32-G594