I'm an expert in Adaptive-Optics (AO) and image processing for astronomy, and I'm currently specializing in Machine Learning for AO data processing. I particularly aim to enhance the science exploitation of AO assisted astronomical instruments that equip ground-based telescopes, through optimal wavefront reconstruction, PSF determination for post-processing of AO images and atmospheric turbulence characterization.

I achieved my PhD graduation supervised by G. Rousset in 2014 at the Observatoire de Meudon, LESIA on the demonstration on laser-based multi-objects adaptive optics (MOAO) with the pathfinder CANARY. I was concentrating on developing on MOAO-specific tomographic control and data analysis tools to finely analyze AO performance over 26 observing nights at the William Herschel Telescope.

I've then got a 1.5 years-long break for teaching fundamental physics in high school at Moissy-Cramayel in France. I was in charge of providing lectures and hands-on experiments on various topics such as electromagnetism, thermodynamics and mechanics.

In 2016, I've got back in the AO field thanks to a post-doctoral opportunity at the Aix-Marseille University (AMU) and Laboratoire d'Astrophysique de Marseille (LAM) to work on Point Spread Function (PSF) reconstruction for tomographic systems. I was supervised by C.M. Correia and collaborated with W.M. Keck Observatory to achieve science verification on the NIRC2 near infra-red imager.

Since 2020, I'm a post-doctoral researcher at LAM /CNRS and I'm strongly involved in the APPLY ANR project. I'm leading the WP2 dedicated to Machine learning solutions for PSF determination. I also have side-projects on wavefront reconstruction and atmospheric profiling using Convolutional Neural Networks. I'm also involved in multiple international large consortia, such as HARMONI, MOSAIC and MAVIS for which I'm responsible of the Data processing and PSF estimation WP.