I’m a 5th-year PhD student in UC Berkeley’s BAIR, co-advised by Prof. Michael Mahoney and Prof. El Ghaoui. My research focuses on leveraging mathematical optimization to incorporate and analyze structure in learning systems.
I’m currently a Student Researcher at Google Research, hosted by Fabian Predregosa, remotely in Montréal. I’m a member of the French Armament Corps (DGA, i.e. French DARPA Fellowship). I enjoy applying my research to industry problems: I’ve interned at Bloomberg LP, Shift Technology, and was a part time researcher at SumUp Analytics.
PhD in Electrical Engineering and Computer Science
UC Berkeley, BAIR
MSc in Machine learning (MVA), 2017
ENS Paris-Saclay
Diplôme d'Ingénieur, 2017
Ecole polytechnique
06/2021: I’m interning at Google Brain Montréal for the summer, hosted by Fabian Pedregosa! I’ll be working on optimization methods tied to program synthesis. Keep posted!
10/2020: We’ve open sourced CHOP, our optimization library built on Pytorch. CHOP contains methods for constrained and composite optimization, with a focus on 1) generating adversarial examples, 2) training sparse and structured neural networks.
06/2020: Our paper Stochastic Frank-Wolfe for Constrained Finite-Sum Optimization (G. Negiar, G. Dresdner, A. Y. Tsai, L. El Ghaoui, F. Locatello, R. Freund, F. Pedregosa) was accepted to the ICML 2020 main conference!
03/2020: I’m a finalist for the Two Sigma PhD Fellowship!
01/2020: Our paper Linearly Convergent Frank-Wolfe with Backtracking Line-Search (F. Pedregosa, G. Negiar, A. Askari and M. Jaggi) was accepted to AISTATS 2020!
Making Frank-Wolfe algorithms practical and scalable.