Presentation

PhD Student in Nuclear Physics and Artificial Intelligence

I am currently a PhD student at the CEA (French Atomic Energy Commission), affiliated with Université Paris-Saclay. Prior to this, I obtained my Engineering Degree in Computer Science & Big Data from JUNIA ISEN Lille (France), graduating as Valedictorian at the age of 21.

My doctoral research sits at the intersection of Artificial Intelligence and Nuclear Physics. I am addressing the inverse problem inherent in Laser-Induced Breakdown Spectroscopy (LIBS).

Specifically, my work focuses on developing AI-driven methods to reconstruct elemental concentrations from complex emission spectra. The primary objective is to accurately quantify Uranium, Plutonium, and Gadolinium levels by inverting spectral data through advanced machine learning techniques.

Broadly, my research interests include:

• Optimisation Methods & Metaheuristics
• Applied Artificial Intelligence (specifically Representation Learning)