About me
I’m a PhD student with the SCOOL team at Inria, where I’m exploring the important challenge of making reinforcement learning systems more robust, fair, and privacy-preserving. Under the guidance of Émilie Kaufmann and Debabrota Basu, I’m working on an exciting vision: creating AI that makes good decisions in the real world where algorithms directly impact human lives. This real-world impact is precisely why our systems require responsible design with strong guarantees, ensuring reliability even in unpredictable environments.
I studied at École Normale Supérieure Paris-Saclay, where I developed a deep interest in machine learning and its potential to address real-world problems. My research is driven by two fundamental aims: building AI that directly improves and integrates into human lives, and uncovering what machine learning can teach us about the nature of intelligence itself.
My research path has taken me through some wonderfully diverse territories:
- Watching complex behaviors emerge spontaneously in cellular automata (INRIA Bordeaux)
- Helping farmers make better decisions despite environmental uncertainties (INRIA Lille)
- Teaching computers to restore damaged images by understanding real-world noise (Centre Borelli)
- Designing algorithms that know when “good enough” is actually better than “perfect” (University of Leoben)
- Creating models that mimic how humans track multiple moving objects (INRIA Bordeaux)
I believe AI research is at its most exciting when it combines theoretical insights with practical applications that make a difference. If you’re curious about responsible AI or any of these research areas, I’d love to connect!