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Courses taught at Ecole Polytechnique:

Together with Luca Castelli Aleardi
This is a course on geometric modeling with emphasis on the the fundamental concepts for creating and analyzing shapes on the computer. We start with techniques for generating and representing smooth curves in 2d using B-splines and Bézier curves. We then move to various techniques for shape representation in 3d with special emphasis on triangle meshes and associated methods. At the same time, we introduce methods for shape analysis, including registration segmentation and parametrization. [Course website]
Fall/Winter 2012-2016 at Ecole Polytechnique

Courses taught abroad:
Computing and Processing Correspondences with Functional Maps,
This course introduces the audience to the techniques for computing and processing correspondences between geometric objects, such as 3D shapes, images or point clouds based on the functional map framework. We will provide the mathematical background, computational methods and various applications of this framework.
[SIGGRAPH 2017 course website] [SIGGRAPH Asia 2016 course website]
courses at SIGGRAPH Asia 2016, and SIGGRAPH 2017.
Digital Geometry Processing,
This course introduces the fundamental concepts for creating and analyzing 3D shapes on the computer. Throughout the course, we put special emphasis on techniques that are based on discrete Laplace operators, which have, remarkably, permeated all areas of discrete shape processing. We will start with the basics of surface reconstruction from point clouds, and point cloud registration (alignment). We will then move to various approaches to shape analysis and processing, including the definitions and applications of various discrete differential geometry operators. [Course website]
Spring 2015 at the University of Verona
Courses TA'ed at Stanford:

Course taught by Alex and Michael Bronstein
The course is a self-contained comprehensive introduction to analysis and synthesis of non-rigid shapes. The course addresses problems such as deformation-invariant similarity and correspondence of shapes, partial similarity, multidimensional scaling methods and their use for invariant representations of non-rigid shapes, spectral methods and the Laplace-Beltrami operator, extrinsic and intrinsic symmetry detection among others. [Course website]
Winter 2009 at Stanford University
Course taught by Leonidas Guibas
This course introduces, at an elementary level, a set of mathematical and algorithmic ideas rooted in geometry which are important in all branches of the computer science dealing with representations and manipulations of virtual physical objects. Included in this list is computer graphics, computer vision, robotics, computational structural biology, and sensor networks . The emphasis is on algorithms and data structures for modeling the shape and motion of physical objects, and more generally multi-dimensional data. The ideas are also important in other computational domains where geometric ideas play an important role, such as in machine learning, statistical data analysis, and databases. [Course website]
Spring 2009 and Spring 2010 at Stanford University