Aram-Alexandre Pooladian
Center for Data Science, New York University

I am a second-year PhD candidate 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.
During my stay at McGill this summer, I’m co-organizing the McGill OPT+ML Summer Seminar series, alongside Courtney Paquette and Elliot Paquette. This past spring semester, I organized the Graduate Student Seminar Series at CDS. If you’re interested in giving a presentation in the future, please reach out!
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
May 15, 2022 | Our paper “Debiaser Beware: Pitfalls of Centering Regularized Transport Maps” was accepted to ICML 2022! |
Dec 13, 2021 | Won “Best Paper Award” at the Optimal Transport and Machine Learning (OTML) workshop at Neurips 2021! |