Michael is a PhD student in the Ciela institute of l’Université de Montréal. His research interests in machine learning are centered around using deep generative models such as diffusion models in order to solve inverse problems in the sciences, in particular, in astronomy. His astronomy research interests revolve around measuring black hole masses and cosmological parameters using strong gravitational lensing. His current work uses radio interferometry to tackle this observational task. He has also developed a new galaxy cluster-finding algorithm for optical survey telescope data under the supervision of Jeffrey Newman at the University of Pittsburgh, where he received his Bachelor’s degrees in Astrophysics and Russian.
Link to ORCiD: https://orcid.org/0000-0001-5200-4095