Professional Experience

  • Research Associate in Atmospheric Physics, NOAA - Cooperative Remote Sensing Science and Technology Center, Remote Sensing of Climate Group, The City College of New York, New York, USA. (2007 to present).
  • Postdoctoral Fellow, NASA Modeling, Analysis and Prediction Program, Institute for Terrestrial and Planetary Atmospheres, School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, USA. (2006 to 2007)
  • Research Engineer in Scientific Computations, Laboratoire de Météorologie Dynamique (LMD) , Ecole Normale Supérieure (ENS), Paris, France. (2004 to 2006)
  • Qualifications

  • PhD in Applied Mathematics and Applied Physics, Numerical simulations of aero-optical effects in compressible turbulent flows, University of Paris XIII, 2001-2004 (Supervisor: Pr. Claude Basdevant, LMD/ENS).
  • Certificate in Astrophysics, University of Paris XI (2000-2001).
  • Master's Degree in Physics / Applied Mechanics, National Institute of Applied Sciences, Rennes, France (1997-1999).
  • Bachelor's Degree in Physics, University of Rennes I, Rennes, France (1994-1997).
  • Computing skills

  • Very good knowledge of Fortran 77/90
  • Good knowledge of C programming and Matlab
  • Very good knowledge of UNIX, LINUX, SHELL
  • Very good knowledge of Office and Windows
  • Very good knowledge of LATEX, IDL, GRADS, TECPLOT, Xmgrace
  • Good Knowledge of NetCDF and Grib formats
  • Experience in analysis and treatment of geophysical data (simulations/observations)
  • Experience on ONERA's super computer NEC-SX5
  • Simulations on Linux clusters via MPI (36 nodes)
  • Experience in CFD, atmospheric and meteorological models: Pegase, Flu3m, SAM, WRF
  • Experience in observational data: ISCCP D1, ISCCP-FD, GPCP, GSSTF2, ERA40, NCEP/NCAR Reanalysis, NCEP/DOE Reanalysis 2
  • Very good knowledge of HTML
  • Good knowledge of CSS
  • Implementation of professional web sites (VASCO Campaign, AMMA Campaign, Remote Sensing of Climate Group)
  • Teaching Experience

  • Fall 2009: Scientific Programming in Remote Sensing: Applied Statistics and Data Analysis (Master and Doctoral levels)
  • Topics: During this course, students learnt how to apply statistical analysis methods to learn something about and from observational data and how to use fundamental programming skills as a tool for working with data and plotted results.
    Professional Affiliations

  • American Meteorological Society Member
  • American Geophysical Union Member
  • Reviewer

  • Journal of Geophysical Research - Atmospheres
  • Journal of Climate
  • National Science Foundation