Daniel Mimouni

I am a PhD student in Applied Mathematics at Mines Paris (CMA) and IFP énergies nouvelles (Applied Mathematics Department), under the supervision of Welington de Oliveira, Paul Malisani and Jiamin Zhu.

Through our objective of solving optimization problems under uncertainty in energy management, we explore, leverage, and enhance techniques in optimal transport, machine learning (mostly RL), convex optimization, and stochastic optimization algorithms.

I am dedicated to combining theoretical research in optimization with practical applications across industries, including energy, biomedical sciences, and technology-driven fields.

Contact: daniel.mimouni@ifpen.fr

🔧 Open-Source Projects

I am committed to reproducible research and open science. All the algorithms developed during my PhD are released as open-source Python packages, each carefully structured, documented, and benchmarked. These repositories reflect both the theoretical depth of my work and its practical implementation in real-world applications such as energy management.

• Computing-Wasserstein-Barycenters-MAM
  Implementation of the MAM algorithm (published in SIMODS 2024), based on Douglas-Rachford operator splitting. Computes exact Wasserstein barycenters efficiently for both fixed and free supports, in balanced and unbalanced settings.

  

• Constrained-Optimal-Transport
  Extension of the above to constrained barycenter problems (PJOPT 2025). The repo includes methods for convex and non-convex constraints, and illustrates how optimization structure can be preserved in the transport formulation.

  

• Nested_tree_reduction
  Codebase implementing a 10× faster version of the nested Wasserstein-based scenario tree reduction algorithm (submitted to Annals of OR). Offers modular tools to apply it in stochastic optimization workflows.

  

• EMS-RL-DRO
  A full-stack implementation for solving multi-stage energy management problems using Reinforcement Learning and Distributionally Robust Optimization. The project includes scenario generation, benchmarking environments, and is being integrated into IFPEN’s EMS-Lab solver.

Each repository is designed to be plug-and-play, with clean APIs, example notebooks, and thorough documentation. They are actively maintained and open to contributions.

News

• [July 26th - August 1st, 2025] I present a boosting method to reduce scenario trees using Optimal Transport at ICSP: Int. Conference on Stochastic Optimization in Paris.
• [July 18th-25th, 2025] I present robust strategies for Energy Management Systems including RL and Distributional Robust Optimization in multistage at ICCOPT: Int. Conference on Convex Optimization in Los Angeles.
• [May 19th-31st, 2025] Working on optimisation and Optimal Transport projects at the Optimal Transport Summer School with Gabriel Peyré, Filippo Santobrogio, Guillaume Carlier, Jalal Fadili, Emilie Chouzenoux and others.
• [November 19th-20th, 2024] Presentation during the PGMO days, the annual conference of the Optimization, OR, and Data Science program of the FMJH Fondation Mathématiques Jacques Hadamard. I present my lattest works about a new approach for Scenario Tree Reduction via Wasserstein Barycenters.
  
• [July 21st-28th, 2024] I take part in the 25th International Symposium on Mathematical Programming in Montreal, Canada, where I present my work on a new approach to efficiently compute the Wasserstein Barycenter for discrete probability measures (balanced and unbalanced and with extending settings). I present in the session Advances in Variational Analysis and Nonsmooth Optimization.
  
• [April, 2024] I visit the Centre of Applied Mathematics in Sophia Antipolis to work closely with Welington de Oliveira and Gregorio Martinez about non-convex and non-smooth extensions within the Douglas-Rachford method framework.
  
• [Nov 28th-29th, 2023] Presentation during the PGMO days, the annual conference of the Optimization, OR, and Data Science program of the FMJH Fondation Mathématiques Jacques Hadamard. I presented a first new method to compute the Wasserstein Barycenter in the balanced setting.