Ankur Moitra, PhD, is an assistant professor of applied mathematics at MIT, and a principal investigator at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). Prior to that, he was an NSF CI Fellow at the Institute for Advanced Study, and also a senior postdoc in the Computer Science Department at Princeton University. He completed his PhD and MS at MIT in 2011 and 2009 respectively, where he was advised by Tom Leighton and was supported by a Fannie and John Hertz Foundation Fellowship. His thesis introduced the notion of vertex sparsification–given a gigantic communication network, but only a small number of terminals that want to use the underlying network to communicate, there is in fact a much smaller network (that can be written down on a sheet of paper) that approximates all the relevant communication properties of the original network. This approach challenges the assumption that algorithms need to be designed to run quickly on massive graphs, since given a small vertex sparsifier algorithms can be run on the graph as a proxy for running on the original network. In 2007 as an undergrad, Ankur received his BS in electrical and computer engineering from Cornell University.
Ankur is the recipient of numerous awards underscoring his academic and professional career: the George M. Sprowls Award (best thesis), the William A. Martin Award (best thesis) for his doctoral and master’s dissertations; in 2015, the NSF CAREER Award; in 2016, the Sloan Research Fellow Award. He has worked in numerous areas of algorithms, including approximation algorithms, metric embeddings, combinatorics and smoothed analysis, but lately has been working at the intersection of algorithms and machine learning.
