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 working on machine learning methods for numerical modeling with a focus on physical oceanography.

Google Scholar Profile

Researchgate

News:

• February 2021
  • Webinar for the AI4ES seminars of Barcelona Computing Center link
• January 2021
  • New paper: “Physical invariance in neural networks for subgrid-scale scalar flux modeling” is accepted in Physcial Review Fluids. Paper; code
• December 2020
  • Co-chaired the AGU20 session “Innovation and Exploration in Observed and Model Oceanographic Data Using Interpretable Machine Learning”
  • Two posters in AGU20
• November 2020
  • New paper: “A Deep Framework for Eddy Detection and Tracking From Satellite Sea Surface Height Data” is accepted in IEEE Transactions on Geoscience and Remote Sensing. Paper
• October 2020
  • Poster presentation at the ECMWF-ESA Workshop on Machine Learning
• September 2020
  • Humbled to serve as a Data Challenge chair for Climate Informatics 2020 conference for the second consecutive time. If you want to discover and/or participate, we prepared a public version of the challenge on Codalab.
  • New paper: The CI2020 data challenge paper is accepted in NeurIPS 2020 workshop ClimateChangeAI. Paper;Code
• 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
  • #EGU2020 is online this year! I have an oral presentation about tide-filtering ConvNets and I am also a co-convener of the Machine learning for Earth system modeling session.
• 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
  • New paper: “Learning Generalized Quasi-Geostrophic Models Using Deep Neural Numerical Models” is accepted at the Machine Learning and the Physical Sciences workshop at NeurIPS 2019. Paper; code.
  • Pleased to serve as a Hackathon chair at Climate Informatics 2019 workshop, details
• 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
  • Talk at AI & Climate-Ocean-Atmoshpere workshop; Rennes, France