I’m a research scientist at Deep Render, working in image and video compression. Previously I was a post-doc at McGill University, in machine learning. My PhD was in applied math, where I was supervised by Adam Oberman. My research interests lie at the intersection of deep learning, machine learning, and applied math.


Jul 18, 2020 Our work on Normalizing Flows and potential functions was featured as a contributing talk at the INNF workshop at ICML
Jul 6, 2020 Started as a research scientist at Deep Render
Jun 11, 2020 New preprint on learning Continuous Normalizing Flows as gradients of potential functions, using Optimal Transport & duality
Jun 1, 2020 "How to train your neural ODE: ..." was accepted to ICML 2020
Apr 23, 2020 Gave a talk at UCLA during the IPAM workshop on PDEs and Inverse Problems in Machine Learning