Yashar Hezaveh is an Assistant Professor in the Department of Physics at Université de Montréal, a Canada Research Chair in Astrophysical Data Analysis and Machine Learning, and a Visiting Fellow at the Center for Computational Astrophysics at Flatiron Institute in New York. He is the founding director of Ciela – Montreal Institute for Astrophysical Data Analysis and Machine Learning. Before his current appointment, he was a Research Fellow at the Flatiron Institute (2018-2019) and a NASA Hubble Fellow at Stanford University (2013-2018).
He is a world leader in the analysis of astrophysical data with machine learning. His current research primarily focuses on Bayesian inference in AI (e.g., diffusion models) to learn about the distribution of dark matter in strongly lensed galaxies using data from large cosmological surveys. His research is supported by the Schmidt Futures Foundation and the Simons Foundation.