About Me
Introduction
I am a CIFRE PhD student in Applied Mathematics & Machine Learning at École Polytechnique, affiliated with the Centre de Mathématiques Appliquées (CMAP) and the SIMPAS team. My work is conducted in collaboration with Michelin, under the academic supervision of Pr. Eric Moulines and Dr. Ahmed Shokry, and the industrial supervision of Dr. Sylvain Desroziers, Dr. Maxime Moreaud and Guillaume Ramelet.
My research focuses on the development of data-driven soft sensors for real-time quality monitoring in rubber production lines. The objective is to overcome the limitations of expensive and offline quality measurements by building predictive systems that provide reliable, online estimations of product quality. This involves the integration of machine learning, uncertainty quantification — notably via conformal prediction —, and explainability to ensure robust deployment in complex industrial environments.
I hold a double master's degree: an MSc in Advanced Computing from Imperial College London, and a Diplôme d'ingénieur in Artificial Intelligence & Data Science from IMT Mines Alès. My training is rooted in applied mathematics, machine learning, and statistical modeling.
I previously conducted research at the Adaptive & Intelligent Robotics Lab at Imperial College, exploring model-based techniques for Quality-Diversity optimization in uncertain environments. Prior to that, I worked at the CNRS CerCo in Toulouse on pathological oscillation detection using CNNs in neurophysiological data. I also contributed to image processing research in collaboration with EuroMov DHM while studying at IMT Mines Alès.
My broader research interests include machine and deep learning, generative modeling, uncertainty quantification, online sensing, and domain adaptation for real-world systems.
Industrial Collaboration Interest
I am keenly interested in forming industrial collaborations during my thesis. As I plan to join industry after my PhD, I'm looking for opportunities to apply my research in practical, real-world settings.
These collaborations could be structured as:
- Focused internship periods
- Regular part-time engagement (e.g., 1-2 days per week)
- Joint research projects with specific deliverables
Areas of particular interest include:
- Manufacturing
- Finance
- BioAI
- Supply Chain
- Neuroscience
- Robotics
If you're interested in collaborating or discussing potential applications of my research, please contact me.