Machine Learning
My research using machine learning is mainly focused on geoscience and on how to use ML frameworks in unconventional contexts.
Geostatistics
My research in geostatistics mainly focuses on statistical simulations. More precisely, I develop new algorithms in Multiple‑Point Statistics (MPS) and machine learning to generate complex structures.
Remote sensing
Remote sensing has had a huge impact on my career and remains important to me. Currently, most of my work in remote sensing is done through collaborations on different projects: vegetation evolution (Vietnam and Valais), growing season, frozen lakes, and even the evolution of ocean NPP (net primary productivity). Many of these studies are run on online platforms such as Google Earth Engine, which enable analyses on very large datasets.
Research philosophy
I put particular importance on investigating cutting‑edge solutions, from both technological and algorithmic perspectives. Most applications of these solutions are done through collaborations.
Furthermore, I put particular effort and time into making the results of various studies available to the community through functional, open, and easy‑to‑use software and libraries.
The full quote:
“The time may not be very remote when it will be understood that for complete initiation as an efficient citizen of one of the new great complex world wide states that are now developing, it is as necessary to be able to compute, to think in averages and maxima and minima, as it is now to be able to read and to write.”