Maks Ovsjanikov

I am a professor in the Computer Science department at Ecole Polytechnique in France. I am a member of the GeoViC group at the LIX research laboratory of Ecole Polytechnique and an associate member (external collaborator) of the DataShape team at INRIA. My current research is mainly supported by my ERC Starting Grant: EXPROTEA.

My research is primarily related to geometric (3D) shape analysis with emphasis on Deep Learning for non-rigid shape comparison and processing. In the past, I have worked on topics including shape classification and retrieval, non-rigid shape-matching, comparison, denoising and symmetry detection especially on 3D point cloud and triangle mesh data. I'm also very interested in image processing, Computer Graphics and Computer Vision in general. You can find some of my work on the Publications page.

Recent News

January 2023

    I'm very happy and honored to have just received an ERC Consolidator Grant for my project VEGA: Universal Geometric Transfer Learning. This project will explore ways in which 3D geometric data can be made more amenable to learning, especially in the presence of limited labeled training data. As always, I'm looking for motivated PhD and Postdoc candidates!

    Two of my outstanding PhD students have successfully defended their PhDs in January 2023:

    • Nicolas Donati with his dissertation on Robust representations for supervised and unsupervised 3D shape matching, and
    • Mariem Mezghanni with her dissertation Structural and Functional Learning for Industrial Design Automatization, done in partnership with Dassault Systèmes.
    Congratulations to Nicolas and Mariem!

December 2022

    Our paper on Functional Maps on Dense Meshes with Robin Magnet has been accepted for publication at Eurographics 2023. This paper presents a scalable approach for computing correspondences across very dense meshes with theoretical guarantees.

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