My habilitation brings together three complementary research axes at the crossroads of experimental physics, data science, and future facilities.
First, I will present my contribution to the CLAS12 experiment, from the development of advanced Micromegas detectors to the very first physics results, including the extraction of a DVCS beam-spin asymmetry.
Then, I will highlight how interpretable Machine Learning techniques can transform particle physics analysis: beyond the opacity of neural networks, I explore transparent algorithms capable of delivering both accuracy and understanding, tested directly on CLAS12 data.
Finally, I will open the discussion toward the future, with innovative experimental concepts to overcome current limitations: measuring recoil proton polarization, probing hadrons through γ-polarimetry, and envisioning electron-ion colliders as the ultimate tool to uncover the pion structure. This journey illustrates how experimental creativity, cutting-edge data analysis, and ambitious projects come together to advance our understanding of the strong force.
Nucleon Structure Laboratory (LSN)
LSN