Hervé BourlardEnseignement et PhD A dirigé les thèses EPFL de Astrid Hagen, Katrin Weber, Todd Stephenson, Jitendra Ajmera, Shajith Ikbal, Mathew Magimai Doss, Mohamed Faouzi Benzeghiba, Mark Barnard, Yann Rodriguez, Hemant Misra, Christos Dimitrakakis, Guillaume Lathoud, Alexei Pozdnoukhov, Agnès Just, Mikaela Keller, Norman Hoon Thian Poh, Dong Zhang, Florent Monay Michaud, Pedro Manuel Da Silva Quelhas, Kevin Smith, Silèye Oumar Ba, Bertrand Mesot, Hamed Ketabdar, David Grangier, Guillermo Aradilla, Jean-François Paie
Aude BillardExpertise
Machine LearningRoboticsMechatronicsDynamical SystemsComputational Neuroscience
Enseignement et PhD Doctorant·es actuel·les Hanli Zhang, Maximilian Schmitz, Luyin Hu, Baiyu Peng, Erfan Etesami, Sthithpragya Gupta, Kuanqi Cai A dirigé les thèses EPFL de Eric Sauser, Sylvain Calinon, Micha Hersch, Florent Günter, Biljana Petreska von Ritter-Zahony, Basilio Noris, Elena Gribovskaya, Seyed Mohammad Khansari Zadeh, Seungsu Kim, Ashwini Shukla, Klas Jonas Alfred Kronander, Luka Lukic, Miao Li, Ravin L
Johanni Michael BreaEnseignement et PhD Doctorant·es actuel·les Aude Maier, Lucas Louis Gruaz, Flavio Martinelli Cours Biological data science II : machine learning BIO-322 Les étudiants comprennent les concepts et méthodes de base d'apprentissage automatique. Ils savent les décrire en termes mathématiques et ils savent les appliquer aux données en utilisant un langage de haut niveau (julia/python/R). Intelligence artificielle et société HUM-286 Ce cours intègre les SHS avec les sciences de l'
Wulfram GerstnerWulfram Gerstner is Director of the Laboratory of Computational Neuroscience LCN at the EPFL. His research in computational neuroscience concentrates on models of spiking neurons and spike-timing dependent plasticity, on the problem of neuronal coding in single neurons and populations, as well as on the link between biologically plausible learning rules and behavioral manifestations of learning. He teaches courses for Physicists, Computer Scientists, Mathematicians, and Life Scientists at the EPFL. After studies of Physics in Tübingen and at the Ludwig-Maximilians-University Munich (Master 1989), Wulfram Gerstner spent a year as a visiting researcher in Berkeley. He received his PhD in theoretical physics from the Technical University Munich in 1993 with a thesis on associative memory and dynamics in networks of spiking neurons. After short postdoctoral stays at Brandeis University and the Technical University of Munich, he joined the EPFL in 1996 as assistant professor. Promoted to Associate Professor with tenure in February 2001, he is since August 2006 a full professor with double appointment in the School of Computer and Communication Sciences and the School of Life Sciences. Wulfram Gerstner has been invited speaker at numerous international conferences and workshops. He has served on the editorial board of the Journal of Neuroscience, Network: Computation in Neural Systems', Journal of Computational Neuroscience', and `Science'.
Nicolas Henri Bernard FlammarionNicolas Flammarion is a tenure-track assistant professor in computer science at EPFL. Prior to that, he was a postdoctoral fellow at UC Berkeley, hosted by Michael I. Jordan. He received his PhD in 2017 from Ecole Normale Superieure in Paris, where he was advised by Alexandre d’Aspremont and Francis Bach. In 2018 he received the prize of the Fondation Mathematique Jacques Hadamard for the best PhD thesis in the field of optimization. His research focuses primarily on learning problems at the interface of machine learning, statistics and optimization.
Pierre VandergheynstPierre Vandergheynst received the M.S. degree in physics and the Ph.D. degree in mathematical physics from the Université catholique de Louvain, Louvain-la-Neuve, Belgium, in 1995 and 1998, respectively. From 1998 to 2001, he was a Postdoctoral Researcher with the Signal Processing Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. He was Assistant Professor at EPFL (2002-2007), where he is now a Full Professor of Electrical Engineering and, by courtesy, of Computer and Communication Sciences. As of 2015, Prof. Vandergheynst serves as EPFL’s Vice-Provost for Education. His research focuses on harmonic analysis, sparse approximations and mathematical data processing in general with applications covering signal, image and high dimensional data processing, computer vision, machine learning, data science and graph-based data processing. He was co-Editor-in-Chief of Signal Processing (2002-2006), Associate Editor of the IEEE Transactions on Signal Processing (2007-2011), the flagship journal of the signal processing community and currently serves as Associate Editor of Computer Vision and Image Understanding and SIAM Imaging Sciences. He has been on the Technical Committee of various conferences, serves on the steering committee of the SPARS workshop and was co-General Chairman of the EUSIPCO 2008 conference. Pierre Vandergheynst is the author or co-author of more than 70 journal papers, one monograph and several book chapters. He has received two IEEE best paper awards. Professor Vandergheynst is a laureate of the Apple 2007 ARTS award and of the 2009-2010 De Boelpaepe prize of the Royal Academy of Sciences of Belgium.
Stefano Francesco BurzioExpertise
Analyse et modélisation des phénomènes naturels non linéaires. équations aux différentielles partielles hyperboliques. Méthodes des éléments finis.
Enseignement et PhD Cours Dynamic finite element analysis of structures ME-473 Le cours présente l'analyse numérique des structures en trois dimensions en utilisant la méthode des éléments finis dans le cadre de l'élasticité linéaire. Les étudiants acquerront une maîtrise des techniques numériques les plus couramment utilisées en dynami
