• [Nov. 2020] Master internship opportunity in spatial oceanography: “Estimation of parameters describing vortices of tropical cyclones from satellite measurements“, Brest (more details here)
  • [Oct. 2020] Master internship opportunity in spatial oceanography and machine learning: “Joint interpolation of satellite Sea Surface Salinity (SSS), Temperature (SST) and Height (SSH) using analog forecasting“, with LOPS, IFREMER and IMT Atlantique, Brest (more details here)
  • [Oct. 2020] Paper in the Quarterly Journal of the Royal Meteorological Society: “Model error covariance estimation in particle and ensemble Kalman filters using an online expectation-maximization algorithm” (more details here)
  • [Sep. 2020] Paper in the Journal of Geophysical Research Oceans: “Spectral Characterization of the Transfer Function between SST and SSH” (more details here)
  • [Sep. 2020] Paper in Natural Hazards: “Wave Group Focusing in the Ocean: Estimations using Crest Velocities and a Gaussian Linear Model” (more details here)
  • [Sep. 2020] Paper in the Journal of Atmospheric and Oceanic Technology: “An Adaptive Optimal Interpolation based on Analog Forecasting: Application to SSH in the Gulf of Mexico” (more details here)
  • [Sep. 2020] Review paper in the Monthly Weather Review: “A Review of Innovation-Based Methods to Jointly Estimate Model and Observation Error Covariance Matrices in Ensemble Data Assimilation” (more details here)


  • Since 2019: associate researcher at the Data Assimilation Research Team, RIKEN Center for Computational Science (Kobe, Japan)
  • Since 2015: associate professor at IMT-Atlantique (Brest, France) and researcher at lab-STICC (French CNRS laboratory)
  • 2012-2015: postdoctoral researcher on spatial oceanography and statistics at Télécom Bretagne (Brest, France)
  • 2010-2012: postdoctoral researcher in data assimilation at the Atmospheric Science Research Group, Univ. Corrientes (Argentina)
  • 2007-2010: PhD at the Oceanography from Space Laboratory of IFREMER (Brest, France)

Research topics:

— Data assimilation:

— Remote Sensing:

— Climate change, renewable energies and risk assessment:

Teaching activities:

  • Probability and statistics (40h/year)
  • Machine learning and deep learning (20h/year)
  • Big data and cloud computing (30h/year)
  • Data assimilation (30h/year)


  • Ocean Remote Sensing Synergy (summer school)
    2014-2015-2016-2018-2019, Brest, France, more details here
  • Data Science & Environment (workshop + summer school)
    2017, Brest, France, more details here
  • Statistical Modeling and Machine Learning in Meteorology and Oceanography (workshop)
    2019-2020, Brest, France, more details here
  • Data Science for Geosciences (doctoral course)
    2018-2019-2020, France, more details here