Aram-Alexandre Pooladian
Faculty Advisor(s): Jonathan Niles-Weed
Contact: aram-alexandre.pooladian@nyu.edu
Bio: Aram is a PhD student at the NYU Center for Data Science, supervised by Jonathan Niles-Weed. His research interests lie at the intersection of optimization theory, computational and statistical optimal transport, and problems in deep learning. Prior to joining CDS, he completed a bachelor’s degree in Honors Applied Mathematics and a master’s degree in Mathematics and Statistics, both at McGill University. During his MSc, he worked on problems in convex analysis, mathematical programs with vanishing constraints, and adversarial attacks for deep neural networks. For more information about past and present research interests, see his personal website.