Hi there! My name is Redouane (Red+1 if you like)!

I am interested in Machine learning for oceanic, atmospheric and climate sciences. My PhD thesis consisted in the use of analog methods (K-Nearest Neighbor Regression) to develop a new data-driven approach to tackle data assimilation: the Analog Data Assimilation (AnDA). In parallel to my thesis I investigated the use of deep learning methods for the segmentation of oceanic eddies from satellite-derived sea related maps.

Currently, I am a postdoc at IGE (Institut des Géosciences de l’Environnment) at Grenoble, France. My postdoc is funded by CNES (French Space Agency). I try to use machine learning methods for the inversion of SWOT data (CNES/NASA mission).

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