- November 19, 2024:
Our paper Adaptive Partitioning for Chance-Constrained Problems with Finite Support is accepted at SIAM Journal on Optimization.
- May 25, 2023:
I started a Postdoctoral researcher position at Polytechnique Montreal under the supervision of Prof. Thibaut Vidal.
- November 7, 2022:
I successfuly defended my PhD entitled Adaptive Refinement Algorithms for Optimization Problems in Energy Transport Networks.
- February 24, 2022:
We (jointly with Diego Cattaruzza, Martine Labbé, Matteo Petris, and Martin Schmidt) have won the scientific prize for the ROADEF/EURO challenge on grid operation based outage maintenance planning.
- November 4, 2021:
I will be presenting my recent work on Adaptive Nonlinear Optimization of District Heating Networks Based on Model and Discretization Hierarchies at the CORE - UCLouvain.
- July 8, 2021:
I will be chairing the MINLP for Energy Networks stream at the EURO 2021 conference.
- April 23, 2020:
Martin Schmidt and I finalized our first joint article entitled Mixed-Integer Nonlinear Optimization for District Heating Network Expansion.
- June 28, 2019:
My Master Thesis has been awarded the second prize of the 2019 IEEE/ICteam Best Master’s Thesis Award.
Marius Roland
Research Associate (Chargé de Recherche) at Inria Lille
Address: Building B, 6 Rue Heloïse, 59650 Villeneuve-d’Ascq, France
Address: Building B, 6 Rue Heloïse, 59650 Villeneuve-d’Ascq, France
About Me
I studied Mathematical Engineering at the Université catholique de Louvain, Belgium, where I received my Bachelor’s degree in 6/2017 and my Master’s degree in 6/2019. Afterwards, I received a PhD from Universität Trier where I was supervised by Prof. Martin Schmidt. During my PhD studies my research focused on adaptive refinement algorithms for optimization problems arising in energy transport networks. Following my PhD, I completed a Postdoctoral position at Polytechnique Montreal supervised by Prof. Thibaut Vidal. Starting from January 2025, I am a CRCN permanent researcher at Inria centre at the University of Lille. My research interests lie at the interface of optimization and energy systems, with a particular focus on stochastic programming, mixed integer programming, and machine learning approaches. I am especially interested in developing methodologies that bridge the gap between theoretical optimization and practical energy applications, including exact algorithms designed to iteratively solve smaller-size surrogates that approximate more realistic but computationally challenging models.