Background
After a bachelor degree (2012-2015) of Mathematics in
University of Jean Monnet France, I continued to obtain the Master (2015-2017) of Science in Industrial and Applied Mathematics
(MSIAM) in
University of Grenoble Alpes France. During my masters, I specialised in the applied aspects of probability and statistics, such as global sensitivity analysis for high-dimensional problems, Bayesian parametric and nonparametric method in statistical learning. Since October 2017, I'm doing a PhD within the
Fluminance team of
INRIA Rennes, on stochastic modelling of oceanic dynamics for ensemble forecasting, uncertainty quantification and data assimilation.
Research
My current research is focused on a stochastic parametrization of oceanic mesoscale eddies, particularly in the quasi-geostrophic regime. The aim is to better understand their physical effects on large-scale circulation, to identify their contributions on energy transfer and to characterize the low-frequency variability in realistic ocean models. In general, I also have strong interests in the applications of uncertainty quantification and ensemble data assimilation. Rencently, I participated in the French national LEFE MANU project - Mutiple Scale Ocean Model (MSOM) and in the International ERC program - Stochastic Transport in Upper Ocean Dynamics (STUOD).
Keywords: stochastic modelling, oceanic dynamics, uncertainty quantification, data assimilation
Publications
- Werner Bauer, Pranav Chandramouli, Long Li, Etienne Mémin -
Stochastic representation of mesoscale eddy effects in coarse-resolution barotropic models - In press, Ocean Modelling, Elsevier, 2020.
- Valentin Resseguier, Long Li, Gabriel Jouan, Pierre Dérian, Etienne Mémin, Chapron Bertrand -
New trends in ensemble forecast strategy: uncertainty quantification for coarse-grid computational fluid dynamics - Archives of Computational Methods in Engineering, 2020.
- Werner Bauer, Pranav Chandramouli, Bertrand Chapron, Long Li, Etienne Mémin -
Deciphering the role of small-scale inhomogeneity on
geophysical flow structuration: a stochastic approach - Journal of Physical Oceanography, 2020.
- Pierre Etoré, Clémentine Prieur, Dang Khoi Pham and Long Li -
Global sensitivity analysis for models described by stochastic differential equations - Methodology and Computing in Applied Probability, Springer Verlag, 2019.
