Physics · Cosmology · Machine learning

Yashar Hezaveh

Associate Professor, Department of Physics
Université de Montréal

Director, Ciela Institute · Canada Research Chair in Astrophysical Data Analysis & Machine Learning

Introduction

I study how mass bends light in the cosmos—strong gravitational lensing—and how we can use those distortions to map dark matter and understand galaxy formation. My group develops machine-learning methods to extract faint signals from large surveys and high-resolution observations.

We work at the interface of theory, observation, and computation, with data from facilities including ALMA, Hubble and JWST, and next-generation surveys such as LSST/Rubin.

Recent highlights

  1. Congratulations to Justine Zeghal and the team for MIRA—a spotlight paper at ICML!
  2. Congratulations to Andreas Filipp for submitting his PhD thesis!
  3. Congratulations to Ronan Legin for submitting his PhD thesis!
  4. Congratulations to Missa Barco and Dhvani Doshi for obtaining NSERC PhD scholarships!
  5. Our team organized an AI–data analysis and telescope observing program for high school students! Great work Nicolas Payot, Missa Barco, Auriane Thilloy, and others!
  6. TARP now has 100+ citations! Google Scholar

Highlights

  • Leadership

    Director of the Ciela Institute (computational astrophysics & ML).

  • Research chair

    Canada Research Chair in Astrophysical Data Analysis & Machine Learning.

  • Affiliations

    Associate Member of Mila, Associate Member of Trottier Space Institute at McGill.
    Visiting Scholar Flatiron Institute, NY.

Explore

Our research group at Université de Montréal and the Ciela Institute combines cosmology, strong lensing, and machine learning—working with students and postdocs across observation, theory, and computing. For roles, collaborations, and how to get in touch, visit the team and research pages.