I am currently a Foundations of Data Science (FDS) Postdoctoral associate at Yale University. Prior to this, I had the (immense!) pleasure of completing my PhD at New York University under the supervision of Jonathan Niles-Weed. My thesis can be found here. Before my PhD, I completed my BA and MSc in Applied Mathematics at McGill University, where I worked with Tim Hoheisel and Adam Oberman.

I study statistical and mathematical aspects of data science. My recent work focuses on analyzing and developing methods for large-scale probabilistic inference and generative modeling, often through the lens of optimal transport theory.