Geoffrey Négiar

PhD Student

UC Berkeley, BAIR

Biography

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.

Interests

Machine learning
Optimization
Natural language processing
Cooking
Martial arts

Education

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

News

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!