I am a Foundations of Data Science (FDS) Postdoctoral Fellow 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. Before that, I completed my BA and MSc at McGill University.

I am somewhere between an applied mathematician, statistician, and computer scientist—–the term might be data scientist. During my PhD, I developed tractable yet principled methodologies for large-scale probabilistic inference based on the theory of optimal transport.

Email: aram-alexandre[dot]pooladian[at]nyu[dot]edu