Team

PhD students

Fabrice LusindeEnergy policy and the Democratic Republic of the Congo
Julien BrandoitOn the quest for the perfect RNN cell
Julien HansenAI for defense
Alfaham AbdallahReinforcement learning for complex environments
Louis ColsonAI for defense
Antoine LarbanoisTechno-economic model of the inclusion of Small Modular Reactors in the Belgian energy system
Samy MokeddemGBOML for bi-level optimization and the handling of uncertainty (2024-)
Lize Pirenne Large Language Models for the industry (2023-)
Arthur Louette AI for defense (2023-)
Laurie Boveroux Optimizing complex large-scale scheduling problems using reinforcement learning (2023-)
Matthias Pirlet Artificial intelligence for electricity markets (2023-)

Maurizio Vassallo
Reinforcement learning for smart grids (2022-)
Florent De GeeterBiological models for improving Deep learning (2021-)
Jocelyn Mbenoun Study and optimization of multi-energy systems (2021-)
Samy AttaiharReinforcement learning and microgrids (2015-)

Post-docs

Victor DachetRemote renewable energy hubs (2025-)
Alireza BahmanyarOperation of power systems by levering the concept of safe dynamic operating envelope (2025-) (Part-time position – main employer Haulogy)
Adrien BollandDeep reinforcement learning and decision-making in energy systems (2025-)
Gaspard LambrechtsReinforcement learning for POMDP (2025-)
Bardhyl MiftariGraph-Based Optimization Modelling Language (2025-)
Pascal LeroyAI for defense (2024-)
Guillaume DervalOptimisation for energy systems (2022-)
Raphael FonteneauEnergy and artificial intelligence (2011-)

Others

Thibaut TéchyTechnical assistant
Danielle BontenSecretary

Former PhD

Victor DachetRemote Renewable Energy Hubs: Design, Techno-Economic and Financial Perspectives (2021-2025)
Elie Kadoche Deep reinforcement learning for wind farm control (2021-2025) (co-supervied by Pascal Bianchi)
Bardhyl MiftariTools and Techniques for Efficient Encoding and Analysis of Linear Programming Models (2021-2025) (co-supervised by Quentin Louveaux and Guillaume Derval)
Adrien BollandReimagining Exploration: Theoretical Insights and Practical Advancements in Policy Gradient Methods (2020-2025)
Gaspard LambrechtsReinforcement Learning in Partially Observable Markov Decision Processes: Learning to Remember the Past by Learning to Predict the Future (2021-2025) (co-supervised by Guillaume Drion).
Amina BenzergaHosting capacity of low-voltage distribution networks (2020-2024)
David VangulickContribution to decision making in power system driven by distributed generation. Solutions and implementation based on Distributed Ledger Technology (2015-2024)
Pascal LeroyContributions to multi-agent reinforcement learning (2018-2024)
Antoine DuboisExploring the near-optimal spaces of energy system optimisation models using necessary conditions for better decision making (2018-2023)
Thibaut ThéateArtificial Intelligence Techniques for Decision-Making in Market Environments (2018-2023)
Mathias Berger Low-carbon energy system design: methods, software and applications (2018-2023)
Nicolas VecovenIntroducing biological neuronal dynamics and neuromodulation in artificial neural networks (2017-2022) (co-supervised with Guillaume Drion)
David RaduSiting Strategies for Variable Renewable Generation Assets in Capacity Expansion Planning Frameworks (2017-2021)
Ioannis Boukas Deep Reinforcement Learning for the Control of Energy Storage in Grid-Scale and Microgrid Applications (2016-2021) (co-supervised by Bertrand Cornélusse)
Miguel Manuel de VillenaSmart Regulation for Distribution Networks – Modelling New Local Electricity Markets and Regulatory Frameworks for the Integration of Distributed Electricity Generation Resources (2016-2021) (co-supervised by Raphael Fonteneau)
Frédéric Olivier Solutions for Integrating Photovoltaic Panels Into Low-voltage Distribution Networks (2013-2017) (co-supervised by Raphael Fonteneau)
Vincent François-Lavet Contributions to deep reinforcement learning and its applications in smart grids (2014-2017) (co-supervised by Raphael Fonteneau)
Michael CastronovoOffline Policy-search in Bayesian Reinforcement Learning (2012-2017) (co-supervised by Raphael Fonteneau)
Quentin GemineActive network management for electrical distribution systems (2012-2016) (co-supervised by Bertrand Cornélusse)
Sebastien MathieuFlexibility services in the electrical system (2012 – 2016) (co-supervised by Quentin Louveaux and Bertrand Cornélusse)
Firas SafadiAI and video games (2010-2015) (co-supervised by Raphael Fonteneau)
David Lupien St-PierreContributions to Monte-Carlo Search (2010-2013) (co-supervised by Quentin Louveaux)
Jing DaiFrequency control coordination among non-synchronous AC areas connected by a multi-terminal HVDC grid (2008-2011) (co-supervised by Yannick Phulpin)
Florence Fonteneau – Belmudes Identification of dangerous contingencies for large-scale power system security assessment (2007-2012) (co-supervised by Louis Wehenkel)
Raphael FonteneauContributions to batch mode reinforcement learning (2007-2011) (co-supervised by Louis Wehenkel)

Former post-docs

Alireza BahmanyarSmart operation of distribution networks (2020-2023 )
Ioannis BoukasOptimising flexibility in water systems (2021- 2023)
Michael CastronovoReinforcement learning for energy systems (2017-2022)
Miguel Manuel de VillenaRenewable energy communities (2021)
Hatim DjelassiOptimisation for multi-energy systems (2020-2021)
Yves VanaubelIntelligent computing for future energy systems (2018-2021)
Quentin GemineSmart operation of microgrids (2016-2022)
Sebastien MathieuIntelligent computing for future energy systems (2017-2020)
Gilles MeyerEnergy management systems for microgrids (2016-2018)
Adrien CouetouxReinforcement learning (2014-2016)
Bertrand CornélusseSmart grids (2013-2016)
Aivar SootlaOptimal control and synthetic biology (2014-2016)
Tobias JungReinforcement learning with application to computer networks (2010-2013)
Efthymios KarangelosRisk-based operation of power systems (2012-2014) (co-supervised by Louis Wehenkel)
Francis MaesReinforcement learning (2012)
Emmanuel RachelsonReinforcement learning (2010)