Aram-Alexandre Pooladian
Center for Data Science, New York University
I am a fifth-year PhD student at the Center for Data Science at New York University, where I am fortunate to be advised by Jonathan Niles-Weed. My interests lie at the intersection of optimization theory, computational and statistical optimal transport, and problems in deep learning. My research is supported in part by NSF, NSERC, Google, and most recently, Meta AI Research.
Before joining CDS, I completed my Bachelor’s and Master’s degrees in (applied) mathematics at McGill University, the latter under the supervision of Tim Hoheisel and Adam Oberman.
Email: aram-alexandre[dot]pooladian[at]nyu[dot]edu
news
Dec 7, 2023 | Gave a talk at MIT on a new preprint, hosted by Youssef Marzouk |
Sep 12, 2023 | Co-organizing the Optimal Transport and Machine Learning (OTML) workshop at NeurIPS 2023 – submit your wonderful papers! |