Research chair in data science for Earth, Space and Environmental Sciences at the Grenoble Alpes Data Institute. I received a PhD from the University of Liege (Belgium), where I worked on the development of novel algorithmic techniques for astronomical high-contrast imaging. In particular, I have approached the task of directly imaging exoplanets from a supervised deep learning perspective and proposed the SODINN framework for exoplanet detection.
I wear several hats in my daily work as a research data scientist interested in interfacing scientific data processing and machine learning. On one hand, I draw inspiration from the artificial intelligence (AI) literature to create innovative algorithms for multi-dimensional data processing (e.g. image sequences with temporal, spectral or other additional dimensions). On the other hand, my interest in open research makes me spend a great deal of time developing open-source scientific computing tools, conducting data challenges and spreading the word about open research practices.
I am passionate about the development of effective solutions at the interface between Artificial Intelligence, academia and entrepreneurship for tackling humanity’s biggest challenges.
“If you’re not having fun, you’re not learning. There’s a pleasure in finding things out.”, Richard Feynman.