blake (at) ttic (dot) edu
I am a PhD student in computer science at the Toyota Technological Institute at Chicago (TTIC) advised by Nati Srebro. I expect to graduate in Spring 2021. My research is generally in machine learning and optimization. The primary focus of my PhD research has been 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 coming to 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. From July 2019, I am supported by a Google PhD Fellowship in machine learning.
My Google Scholar page.
Last Updated: June 12, 2018