Welcome to my personal webpage!
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 LOCEAN (IPSL/Sorbonne Université) in Paris, France. My postdoc is funded by Prof. Venkatramani Balaji’s “Make Our Planet Great Again” grant. I am investigating how to use machine learning methods for numerical modeling with a focus on physical oceanography.
Google Scholar Profile
- June 2020
- “Innovation and exploration in observed and model oceanographic data using interpretable machine learning”, our session proposal for #AGU20 is accepted. Please consider our session for submitting your abstracts! Link
- April 2020
- New paper: “Filtering Internal Tides From Wide-Swath Altimeter Data Using Convolutional Neural Networks” is accepted at IEEE IGARSS 2020 conference. Arxiv; code
- March 2020
- February 2020
- New position: Thrilled to join LOCEAN lab at IPSL/Sorbonne Université as a postdoc researcher, will continue my work on machine learning for numerical modeling with a focus on superparametrization problems.
- October 2019
- June 2019
- Invited talk: “Physical Oceanography meets Deep Learning”; Data Science for the future, a workshop of Global Science Week 2019, Grenoble, France.
- April 2019
- The first IndabaXMorocco was a success! Glad to have taken part of the general chair committee.
- Poster presentation at the European Geophysical Union 2019; Vienna, Austria. Abstract
- February 2019