I am a researcher in mathematical optimization with interests in nonlinear and discrete problems, and an emphasis on formulations and computational approaches.

TL;DR: I write mathematical models that represent decision-making processes or equilibria within systems, and build abstract algorithms and concrete computer programs that provide guaranteed solutions of these models.

I joined the Inria Institute in Grenoble in January 2024 as a Tenured Associate Researcher (Chargé de Recherche) working with the Polaris group at the Grenoble Computer Science Lab. Broadly speaking, we work on decision and learning in uncertain, unknown, dynamic contexts, potentially with multiple agents. If what the group and/or what I do sounds like fun, feel free to contact me or check some example topics.

My research interests span the theory, methods, and algorithms for several flavours of mathematical optimization. More specifically, I have been interested in exact solution methods for constrained optimization with constraint structures we can exploit. Those include solution methods, computational models, and software in mixed-integer (non-)linear and convex optimization and in particular around the SCIP framework and Frank-Wolfe related approaches. I have been exploring applications of these classes of problems in power systems, quantum information, systems biology, networks and infrastructure, and data science & machine learning.

I graduated with a double PhD (cotutelle) from 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 spent some time in Berlin as a researcher at the Zuse Institute.

I am involved in several open-source projects around optimization and scientific computing in the Julia programming language and around JuMP. I worked with and 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, transportation systems, the energy transition); a more detailed readling list can be found on my goodread. I also enjoy games in various formats (tabletop, video, board, card) and cooking (from fermentation attempts to pasta recipes and coffee brewing).

  • Bilevel Optimization
  • Convex Optimization
  • Mixed-Integer (Non-)Linear Optimization
  • Power Systems
  • Mathematical Optimization
  • Optimization and Engineering
  • Optimization Software
  • Algorithm Design
  • Optimization in Statistics & Learning
  • 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


Associate Researcher
January 2024 – Present Grenoble, France
Research in optimization.
Postdoctoral Researcher
January 2021 – December 2023 Berlin, Germany
Research in optimization methods and computation.
Doctoral Researcher
Polytechnique Montréal, Inria Lille
September 2017 – December 2020 Montréal, Canada & Lille, France
Double PhD program in mathematical optimization for pricing of Demand Response programs in a smart grid context.
Research Engineer, Data Scientist
Equisense SAS
July 2016 – August 2017 Lille, France
Research and development for a startup building connected devices and associated products for horse-riders.
Master’s Thesis
Siemens AG, Digital Industries
February 2016 – July 2016 Karslruhe, Germany
Stochastic models for event monitoring in automated systems.
Junior Engineer Placement
ArcelorMittal Hamburg GmbH
August 2014 – January 2015 Hamburg, Germany
Quantification and analysis of material losses in a steel rolling mill.


Filter publications here.

(2024). How many clues to give? A bilevel formulation for the minimum Sudoku clue problem. Operations Research Letters.

Cite arXiv

(2024). Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe. Proceedings of the INFORMS Optimization Society Annual conference.

Cite arXiv

(2024). Optimisation models for the design of multiple self-consumption loops in semi-rural areas. arXiv e-prints.

Cite arXiv

(2024). Probabilistic Lookahead Strong Branching via a Stochastic Abstract Branching Model. International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research.

Cite arXiv

(2024). Solving the Optimal Experiment Design Problem with Mixed-Integer Convex Methods. Symposium on Experimental Algorithms.

Cite arXiv

Work with me

If you want to join my group and work with me, please read the information here.


The most reliable way to reach me is per email.