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Research projects
The goal of my thesis is to build a systematic procedure for finding the best performing optimization methods for a given structured problem. This research went into two directions: First, I worked on applications where I analyzed specific structured problems to identify the best performing optimization methods. Second, I focused on developing the systematic procedure mentioned earlier.
A principled approach to automatically recommend optimization methods
With François Glineur, we propose a modeling language that aims at describing oracle-based optimization problem formulations. Using this language, we propose a framework that automatically checks whether a user-provided optimization problem fits a known template. Leveraging on an extensive library of optimization methods with their associated convergence rates, the framework allows automatically ranking applicable optimization methods according to their worst-case theoretical guarantees.
I have presented this work at ISMP2024 (slides) and at ALGOPT2024 (poster).
Faster optimization methods for day-ahead electricity markets
With Yassine Kamri, Mehdi Madani and François Glineur, we conduct extensive benchmarking experiments for CH prices computation on a large panel of first-order methods. We then suggest methods combined with heuristics to most efficiently solve CH pricing.