I am a second year PhD student in the EECS department at MIT, where I am advised by
Aleksander Mądry. My current research interests
are in building more robust and reliable machine learning models. In particular, my goal is to
understand how modern deep learning methods represent data and to identify the biases that they
create. In the past, I've worked on problems in graph theory and the analysis of time series.
I graduated with my BS/MS in Computer Science at Stanford, where I worked with Jure Leskovec and Matei Zaharia. Before starting at MIT, I was a Computer Vision Scientist with Tesla Autopilot.