About me

I am a PhD student in Mathematics and Artificial Intelligence at IP Paris, within the SAMOVAR laboratory.
My research focuses on the security of Reinforcement Learning (RL) models for Beyond 5G (B5G) and 6G networks.

My thesis is part of the PEPR Future Networks program, a French strategic and large-scale research initiative under France 2030, dedicated to advancing next-generations communication technologies.

🔬 Research Interests

I work on Reinforcement Learning (RL) and Multi-Agent Reinforcement Learning (MARL) applied to physical systems, with a heavy focus on Physical AI.
My main motivation lies in understanding and improving the safety, robustness, and reliability of RL methods, both from a technical and a conceptual standpoint.

I particularly enjoy bridging the gap between theory and practice. I like tackling fundamental research questions that remain meaningful for applied use cases, far from the perfect world of toy examples.
What excites me most is being able to follow a project across its entire journey, from theoretical ideas on the blackboard to the first tests on real-world prototypes.

On a side scientific interest, I am also curious about how quantum computing could be an ally to enhance Reinforcement Learning scalabity eventually.

🎓 Previous Academic Background

I hold a Master’s degree in Mathematics and Artificial Intelligence from Paris-Saclay University, where I built strong foundations in statistics, probability, optimization, machine learning, and deep learning.

Before that, I completed a double Bachelor’s degree in Mathematics and Fundamental Physics at Paris-Saclay University, known for its rigorous and demanding scientific curriculum.
This background in physics continues to shape my approach to research and fuels my curiosity for topics such as quantum computing and controlled nuclear fusion for civilian applications.

📄 Learn More

You can find more details in my CV.

Feel free to reach out ! I am always happy to discuss research, collaborations, or simply exchange ideas.