The topics I am working on:

  • Theoretical data assimilation:

    • Methodology in atmospheric chemistry data assimilation: representativeness errors, error estimation, hyperparameter selection.

    • Regularisation of inverse problems by the maximum entropy on the mean principle. Applied information theory.

    • Nonlinear/non-Gaussian data assimilation.

    • Ensemble Kalman filtering, particle filtering.

    • Ensemble variational methods.

    • Multiscale, adaptive grid data assimilation.

  • Machine learning applied to the geosciences, in particular combined with or in support of data assimilation.

  • Inverse modelling of atmospheric tracer source. Applications to Chernobyl, Fukushima, emergency response.

  • Data assimilation and inverse modelling in air quality. Applications to Carbon monoxide, volatile organic compounds, heavy metals, photochemistry.

  • Monitoring network design for air pollution.

  • Air quality numerical modelling (especially radionuclides dispersion).

  • New applications of data assimilation: adaptive optics for extremely large telescopes, detection and attribution in climate.