Ice density image assimilation (north pole) "Avenel et al. Stochastic level set dynamics to track closed curves through image data. Journ of Math. Imaging and Vision, 2014"


Stochastic SQG models "V. Resseguier, E. Mémin, B. Chapron, Geophysical flows under location uncertainty, Part I, II & III 2017"


I am a researcher at Inria where I lead the Fluminance research group. My research focuses on the study of methods for fluid flows analysis from image sequences. This concerns essentially the study of methodologies for the estimation or the tracking along time of features transported by the flow. To that end we rely on methods allowing the coupling between dynamics models and image data. The set up of large scale stochastic dynamical models, the identification of reduced order dynamical models, the devise of dedicated flow measurement techniques, as well as the design of image-based data assimilation frameworks are few research topics related to such an axis of work. This research activity is at the crossing of several disciplines such as Geophysical sciences, Fluid Mechanics, Computer Vision and Applied Mathematics.

Responsabilities and Activities

Leader of the Fluminance group jointly affiliated to Inria, the mathematical research institute of Rennes I University ( IRMAR ) and Inrae

Visiting professor, Department of Mathematics , Imperial College London



tel: 02 99 84 75 15

Personal scholar google page, Research Gate


ERC STUOD awarded (Site)

Last publications

  • G. Tissot, A. Cavalieri, E. Mémin, Stochastic linear modes in a turbulent channel flow, J. of Fluid Mech., In press, PDF .
  • W. Bauer, P. Chandramouli, L. Li, E. Mémin, Stochastic representation of mesoscale eddy effects in coarse-resolution barotropic models, Ocean Modelling, 151: 1--50, 2020, PDF .
  • W. Bauer, P. Chandramouli, B. Chapron, L. Li, E. Mémin, Deciphering the role of small-scale inhomogeneity on geophysical flow structuration: a stochastic approach, J. of Phys. Oceanography, 50 (4): 983--1003, 2020, PDF .
  • P. Chandramouli, E. Mémin , D. Heitz, 4D large scale variational data assimilation of a turbulent flow with a dynamics error model, J. of Comp. Phys., 412 (1): 109446, 2020, PDF .