I am a researcher in computational optimization at the Zuse Institute Berlin, in the AI in Society, Science, and Technology department. I am associated with the MODAL-SynLab DFG project and a member of the MATH+ Berlin Mathematics Research Center.

My research interests span the theory, methods, and algorithms in mathematical optimization, either on various generic or specific classes of problems. Slightly more specifically, I have been interested in structured constrained optimization in various settings (see below for a list of topics). Those include solution methods, computational models, and software in MI(N)LP and convex optimization and in particular around the SCIP framework and Frank-Wolfe related approaches.

I graduated with a double PhD (cotutelle) between Polytechnique Montréal, at the GERAD lab and Centrale Lille, at INRIA & the Cristal lab, in mathematical optimization. My thesis focused on bilevel optimization, an extension coined near-optimality robustness, and pricing for demand response in smart grids. It was co-supervised by Luce Brotcorne (INRIA) & Miguel F. Anjos (University of Edinburgh).

I am involved in several open-source projects around optimization and scientific computing in the Julia programming language and around JuMP but like looking around on new development. Before starting the PhD, I worked in various industries, from a hardware startup to steel manufacturing. I did my joint Bachelor-Master in Process Engineering at the UTC in France with a semester at the TUBS in Germany and Polytechnique Montreal.

On a personal note, I read both fiction (mostly history, detective, thrillers and fantasy) and non-fiction books, on economic policy, education, and entrepreneurship, a more detailed list can be found on goodread. I also enjoy games in various formats (tabletop, video, board, card) and cooking.