I’m a research scientist at Samsung SAIT AI Lab Montreal, an academic-style research lab situated within Mila - Quebec AI Institute. My research revolves around foundational aspects of deep learning algorithms, with a focus on understanding and improving their robustness and generalization performance. I recently earned a PhD in machine learning at Mila, University of Montreal, advised by Simon Lacoste-Julien.
Prior to my time at Mila, I’ve worked as a theorerical physicist, first as a junior scientist at the Max Planck Institute for Gravitational Physics in Potsdam, then as a Humboldt Fellow hosted by the University of Waterloo and McGill. My work was mainly about quantum gravity and associated mathematical structures from higher dimensional algebra and matrix models. I received a PhD in physics from Perimeter Institute in Waterloo and Ecole Normale Supérieure de Lyon, under the supervision of Laurent Freidel.
I also love teaching. I’ve taught numerous classes in mathematics, physics and computer science as a teacher’s assistant at ENS Lyon and UdeM and as a course lecturer at UW and McGill.
See my curriculum vitae for more details.
PhD, Machine Learning, 2022
Mila, Université de Montréal
PhD, Theoretical Physics, 2009
ENS Lyon and Perimeter Institute, Waterloo
Master's degrees, Mathematics & Physics, 2002-2004
University Paris-Saclay and ENS Paris
Stipendary student, 2002-2004
ENS Paris-Saclay, Mathematics Department