I’m interested in the theory, methods and applications of mathematical optimization, trying to find the provably best solution to a given problem. More specifically, I have been interested at constrained optimization in various settings (see below for a list of topics).
My thesis, defended in December 2020, focuses 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 in scientific programming. Before starting the PhD, I worked in various industries, from an IoT startup to steel manufacturing. I did my joint Bachelor-Master in Process Engineering at the UTC with a semester at the TUBS and Polytechnique Montreal.
On a personal note, I read both fiction (mostly detective, thrillers and fantasy) and non-fiction books, on economic policy, strategy, and entrepreneurship (a more detailed list can be found on goodread. I also enjoy games in various formats (tabletop, video, board, card) and cooking.
Joint PhD, Applied Mathematics & Computer Science, 2017-2020
Polytechnique Montreal, INRIA, Centrale Lille, GERAD
Joint Bachelor & Master of Science in Process Engineering, 2011-2016
University of Technology of Compiègne (UTC), France
Exchange program, applied mathematics, computer science & industrial engineering, 2015
Polytechnique Montréal, Canada
Exchange semester, Process & Energy Engineering (Bachelor), 2013
Technische Universität Braunschweig, Germany
Research and development for a startup building connected devices and associated products for horse-riders.
Quantitative methods for the identification of root causes for steel loss on a rolling mill plant.
Different projects, open-source and academic.*