About

I’m a PhD student in computer science at the University of Montpellier, since 2020. My research topic is about estimating the evolution of poverty, especially in developing countries, with satellite image times series and deep learning. The idea is producing a model that processes satellite image time series of some place on earth, and estimates the poverty evolution observed in this location. Satellite image time series are a rich source of informations, combined with recent deep learning approaches, a model could identify the evolution of key structures (like roads, hospital, lakes, buildings, …) and learn the dependency with the evolution of poverty.

Background overview

After high school, I studied mathematics at the university of La Rochelle in France. I obtained a BS degree in mathematics and a MS degree in Mathematics and Applications. Then I went in Montpellier to start my PhD. Around that, I learn programming with Python, and famous libraries like Tensorflow and Opencv. I have put this learning to use during my research. During my PhD, I have become familiar with public satellite images (Landsat/Sentinel) and also with Nighttime lights map of the world (DMSP/VIIRS). I have a good knowledge on deep learning in general, particularly on sequence models.