Louis Berthier

I am a PhD student in Applied Mathematics and Machine Learning at Ecole Polytechnique, within the Centre de Mathematiques Appliquees (CMAP) and the SIMPAS team. My research is a CIFRE collaboration with Michelin, supervised by Pr. Eric Moulines, Dr. Ahmed Shokry, Dr. Maxime Moreaud, and Guillaume Ramelet.

I build adaptive systems that predict product quality in real time on the factory floor, replacing costly offline laboratory measurements with machine learning models that know when to trust their own predictions. My work sits at the crossroads of machine learning, uncertainty quantification (especially conformal prediction), and explainability, with the long-term goal of enabling autonomous process control in manufacturing.

Before my PhD, I explored machine learning across several domains:

• Robotics — Adaptive & Intelligent Robotics Lab, Imperial College London: sample-efficient Quality-Diversity optimization with surrogate models
• Neuroscience — CNRS CerCo: deep learning for pathological oscillation detection in epileptic EEG signals
• Healthcare — EuroMov DHM: image processing and biomedical signal analysis

Collaboration

I enjoy bridging academic research and real-world applications. Alongside my PhD, I collaborate with startups and industry partners on applied ML challenges, from agentic systems to computer vision at scale to uncertainty-aware prediction systems.

If you have a problem where reliable machine learning could make a difference, I’d love to hear about it. Possible formats range from research internships and consulting to joint projects with concrete deliverables.

Domains of interest: healthcare, manufacturing, robotics, neuroscience, bioAI, retail, finance, supply chain.

Interested? Let’s talk.