Welcome to my homepage. I am a researcher at Ecole Polytechnique with a particular focus on learning functional mapping between images or 3D data or even graphs and its extension to control theory (e.g. non-linear dynamics with koopman operator), supported by Maks ERC grant. Previously, I was a Marie Curie Early Stage researcher for about a year in the famous Computer Vision Dept. (Bernt Schiele et al.) at MPI for Informatics, Saarbrucken. Before that, I graduated with a Masters degree in Applied Math with distinction and a training in machine learning and computer vision MVA Masters programme. Before that, I was somewhat fortunate to be hired by Catherine at CNRS, Francois Fleuret at Idiap/EPFL, and Jean Ponce at INRIA/ENS.
I gave an invited talk on ‘Learning based correspondence’ at SGI’21 by MIT
Learning Symmetry aware Canonical Embedding Preprint here
Low Rank Matrix Decomposition on Graphs Preprint here
We got another best paper award Nomination, this time at CVPR 2020! Top 26 out of 6000 submissions.
We got a Best Paper Award Nomination( 7 out of 4000 +) at ICCV 2019.
I came back to academia, joined Ecole Polytechnique (March,2019) and gave an invited lecture on deep autoencoders to second year Polytechnique students.
presented Foreground Clustering at Neurips 2018.