Past programs

Interdisciplinary seminar

Program 2022 :
Sept. 08th : Erhart polynomials and code optimization - Philippe CLAUSS and Thomas DELZANT
Sept. 22nd : Drums shape and room acoustics - Antoine DELEFORGE and Yannick PRIVAT
Oct. 06th : Dynamical systems and astrophysics - Giacomo MONARI and Ana Rechtman
Oct. 22nd : Causal inference and applications - Marianne CLAUSEL and Etienne BIRMELE
Nov. 10th : Elliptic curves, symbolic proofs and electronic vote - Véronique CORTIER and Pierrick GAUDRY
Nov. 24th : On mesh generation - Frédéric ALAUZET and Pierre KRAEMER
Dec. 08th : Fluid flow simulation and multi-scale spray modelling - Agathe CHOUIPPE and Marc MASSOT


Program 2021 :
Sept. 09th : Discrete differential geometry and applications - Franck HETROY-WHEELER and Mathieu DESBRUN
Sept. 23rd : Symplectic geometry and astrophysics - Rodrigo IBATA and Alexandru OANCEA
Oct. 07th : Turbulence, aeronautics and fluid-particle dynamics - Abderhamane MAROUF and Markus UHLMANN
Oct. 21th : Lung ventilation modelling and high performance computing - Céline GRANDMONT and Hugo LECLERC
Nov. 04th : Discrete geometry for images and point clouds - Etienne BAUDRIER and Quentin MERIGOT
Nov. 18th : Wavelets and astrophysics - Erwan ALLYS and Philippe HELLUY
Dec. 02nd : Optimal transport and astrophysics - Nicolas JUILLET and Bruno LEVY

Summer school

28/08/2023 - 01/09/2023 : Geometry and Data

Optimal transport for data analysis - Laetitia CHAPEL
Shape analysis - Joan GLAUNES
Topological methods for astrophysical data - Katarina KRALJIC
Nonlinear, Geometric Reduced Models for Forward and Inverse Problems - Olga MULA
Geometric transformations on digital images - Phuc NGO
Coverage of astronomical datasets - Sébastien DERRIERE
Multi-scale modeling of natural images with stochastic geometry - Sixin ZHANG


29/08/2022 - 02/09/2022 : Deep Learning and Applications

Introduction to Deep Learning - Léo BOIS
Convolutional Neural Networks for object dectection: fast and accurate results with the YOLO (You Only Look Once) method - David CORNU
Generative models for images - Bruno GALERNE
Deep Learning and dynamical systems: applications in neuroimaging - François ROUSSEAU
Introduction to deep learning on graphs - Samuel VAITER
Rodrigo IBATA
Nicolas PADOY

UFR de mathématique et d'informatique
Faculté de physique et ingénierie
Observatoire astronomique de Strasbourg