blakewoodworth (at) gmail (dot) com
Since October 2021, I have been a postdoctoral researcher with the SIERRA team at Inria, working with Francis Bach.
Before that, I was a PhD student in computer science at the Toyota Technological Institute at Chicago (TTIC) advised by Nati Srebro, and I graduated in Summer 2021. The primary focus of my PhD research was in the theory of optimization, with a particular emphasis on precisely understanding the oracle complexity of convex, non-convex, and distributed optimization problems. In addition to my work in optimization, I have also been interested in efforts to understand modern, highly overparametrized machine learning models through the lens of implicit regularization. Earlier in my PhD, I also enjoyed working on fairness in ML and on adaptive data analysis.
Before TTIC, I studied at Yale University where I received a B.S. in computer science, advised by Dan Spielman. At Yale, my coursework was spread evenly across the computer science, mathematics, and statistics departments; I was also a peer tutor for several programming-intensive computer science courses.
From September 2017-July 2019 I was supported by a NSF Graduate Research Fellowship, and from July 2019-August 2021, I was supported by a Google PhD Fellowship in machine learning.
My Google Scholar page.
Last Updated: April 22, 2022