Brian Bullins received his PhD in computer science from Princeton University in 2019. Previously, he completed his undergraduate degree at Duke University in 2014 as a Benjamin N. Duke Scholar, where he received a B.S. in computer science and an A.B. in mathematics.
His research interests broadly lie in both the theory and practice of optimization and machine learning. In particular, his work on improving matrix estimation techniques has led to new higher-order methods for convex and non-convex optimization with provable guarantees.
Dr. Bullins also has a personally maintained website which can be found at http://www.ttic.edu/bullins.