I am a PhD candidate in a double program (cotutelle) between École Polytechnique of Montréal, at the GERAD lab and Centrale Lille, at INRIA & the Cristal lab, in mathematical optimization for pricing applications in smart grids. I am currently on an academic visit at the School of Mathematics at the University of Edinburgh.
My thesis focuses on bilevel optimization, robust extensions and pricing for demand response. Other topics I look at include non-linear optimization & applications in engineering, integer optimization & decompositions, game theory and optimization applications in statistics & learning.
I am involved in several open-source projects around optimization and scientific computing, mostly in the Julia programming language. 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.
On a personal note, I read both fiction (mostly detective, thrillers and fantasy) and non-fiction books, generally on economic policy, strategy and entrepreneurship (a more detailed list can be found on goodread. I also games in various formats (tabletop, video, board, card).
I will be looking for a position to start in 2021. Although I am primarily looking at positions in academic environments and research institutes, I am open to research-intensive environments with projects on the topics mentioned above. My academic CV is available upon request.
Joint PhD, Applied Mathematics (Polytechnique Montreal) & Computer Science (Centrale Lille)
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
École Polytechnique de 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.*