I am currently a resident with the Google Brain team working on aspects of machine learning. Thus far, my work has focused on using notions from statistical physics to better understand neural networks.
Recently, I completed my Ph. D. in Physics working with Andrea Liu at the University of Pennsylvania. My graduate work focused on understanding the behavior of disordered solids and glassy liquids from their structure. Central to our approach has been the use of machine learning to identify local structural motifs that are particularly susceptible to rearrangement.
Additionally, I have spent some time studying the properties of experimental colloidal systems, length scales in Jammed solids, and spin systems whose target spaces have interesting topology.
On the side, I have worked on a few smaller projects including: a real-time GPU raytracer using WebGL and a study of how upvotes are given on Reddit.