Alexandre Adam, Ph.D.

Alexandre Adam is a Flatiron Research Fellow at the Center for Computational Mathematics and the Center for Computational Astrophysics. His research develops machine-learning and Bayesian methods for astronomical imaging, with a particular focus on strong gravitational lensing and the small-scale structure of dark matter. His recent interest is in using information geometry and differentiable simulators to understand which features of strong gravitational lensing data can be reliably measured. He received his Ph.D. in physics from the Université de Montréal, where he worked on diffusion models and high-dimensional Bayesian inference methods.