Sixuan Sven WangEnseignement et PhD Doctorant·es actuel·les Leonardo Nevali Cours Bayesian statistics MATH-339 Une première introduction aux statistiques bayésiennes, supposant des connaissances issues des cours de base en statistiques et en probabilité. Nous mettrons l'accent sur les aspects statistiques et mathématiques fondamentaux.
Jean-Marc OdobezEnseignement et PhD Doctorant·es actuel·les Vivek Samir Gupte, Yesmine Abdennadher, Samy Tafasca, Shalutha Navindu Rajapakshe Rajapakshe Mudiyanselage, Gökhan Özbulak, Karl El Hajal, Hasindri Sankalpana Watawana, Mingchi Hou, Pierre François Marie Vuillecard, João Pedro Gandarela de Souza, Anirban Mukherjee, Elija Maria Vida, Nawal Haidar, Mojtaba Nafez A dirigé les thèses EPFL de Jagannadan Varadarajan, Alexandre Heili, Samira Sheikhi, Kenneth Alberto Funes Mora, Do Hoang Nam Le, Christian Jaques, Yu Yu,
James HendersonEnseignement et PhD Doctorant·es actuel·les Haruki Shirakami, Dina El Zein, Jose Rafael Espinosa Mena, Kimia Alavi, Mojtaba Nafez A co-dirigé les thèses EPFL de Lesly Sadiht Miculicich Werlen, Rabeeh Karimi Mahabadi, Alireza Mohammadshahi, Andreas Thomas Marfurt, Jan Frederik Jonas Florian Mai, Melika Behjati, Fabio James Fehr, Andrei Catalin Coman Cours Deep Learning For Natural Language Processing EE-608
Michaël UnserExpertise
Image Processing Medical Imaging Biological Imaging Wavelets Splines Multiresolution
Enseignement et PhD Doctorant·es actuel·les Youssef Haouchat, Vincent Patrick Lawrence Guillemet, Bassam El Rawas, Stanislas Ducotterd, Mehrsa Pourya, Zhiyuan Hu A dirigé les thèses EPFL de Stefan Horbelt, Jan Kybic, Maria Arrate Munoz Barrutia, Manuela Feilner, Slavica Jonic, Mathews Jacob, Michael Liebling, Michael Sühling, Muthuvel Arigovindan, François Aguet, Cédric Vonesch, Ildar Khalidov, Sathish Ramani, F
Philippe MüllhauptExpertise
Commande non linéaireThéorie de la commandeMécanique généraleSystèmes dynamiquesStatistique
Mission
Offrir une formation technique et scientifique rigoureuse en commande non linéaire, en mécanique classique et en théorie statistique
Travail en cours
Chercheur et enseignant dans les domaines de l'automatique, la statistique, les systèmes dyanmiques et la mécanique classique.
E MSc. et BSc. en génie électrique (EPFL, 1993) DEA en Automatique et Traitement du Signal (Paris VI, 1994) PhD en Automa
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
Philip Neil GarnerEnseignement et PhD Doctorant·es actuel·les Yesmine Abdennadher, Mutian He, Elija Maria Vida A co-dirigé les thèses EPFL de Mohammadjavad Taghizadeh, Pierre-Edouard Jean Charles Honnet, Sibo Tong, Bastian Schnell, Alexandre Samuel Philippe Bittar, Louise Clothilde Coppieters De Gibson, Haolin Chen
Pascal FuaPascal Fua received an engineering degree from Ecole Polytechnique, Paris, in 1984 and the Ph.D. degree in Computer Science from the University of Orsay in 1989. He then worked at SRI International and INRIA Sophia-Antipolis as a Computer Scientist. He joined EPFL in 1996 where he is now a Professor in the School of Computer and Communication Science and heads the Computer Vision Laboratory. His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and Augmented Reality. His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and machine learning. He has (co)authored over 300 publications in refereed journals and conferences. He is an IEEE Fellow and has been an Associate Editor of IEEE journal Transactions for Pattern Analysis and Machine Intelligence. He often serves as program committee member, area chair, and program chair of major vision conferences and has cofounded three spinoff companies (Pix4D, PlayfulVision, and NeuralConcept).
Giancarlo Ferrari TrecateExpertise
Automatic control, Dependable control, Neural-network Control, Machine learning, Microgrids, Hybrid systems
Mission
See the webpage of the DECODE (Dependable Control and Decision) group.
Teaching & PhD PhD Students Laura Meroi, Julien Pallage, Nicolas Léo Pierre Kirsch, Simone Baratto, Daniele Martinelli, Riccardo Cescon, Jakob Nylöf, Sabri El Amrani Past EPFL PhD Students Pulkit Nahata, Mustafa Sahin Turan, Baiwei Guo, Jean-Sébastien Brouillon, Clara Galimberti, Andrea Martin, Muhammad Zakwan,
Samy BengioExpertise
Algorithmes d'apprentissageTraitement de la parole automatiqueAuthentification de personnesTraitement multimodalTraitement de sequencesReseaux de neurones, support vector machinesModeles de markov caches, mixtures de gaussiennesetc
Expertise
Algorithmes d'apprentissageTraitement de la parole automatiqueAuthentification de personnesTraitement multimodalTraitement de sequencesReseaux de neurones, support vector machinesModeles de markov caches, mixtures de gaussiennesetc
Mission
Samy Bengio est cher
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.
Michael GraetzelProfessor of Physical Chemistry at the Ecole polytechnique fédérale de Lausanne (EPFL) Michael Graetzel, PhD, directs there the Laboratory of Photonics and Interfaces. He pioneered research on energy and electron transfer reactions in mesoscopic systems and their use to generate electricity and fuels from sunlight. He invented mesoscopic injection solar cells, one key embodiment of which is the dye-sensitized solar cell (DSC). DSCs are meanwhile commercially produced at the multi-MW-scale and created a number of new applications in particular as lightweight power supplies for portable electronic devices and in building integrated photovoltaics. They engendered perovskite solar cells (PSCs) which turned into the most exciting break-through in the history of photovoltaics. He received a number of prestigious awards, of which the most recent ones include the RusNANO Prize, the Zewail Prize in Molecular Science, the Global Energy Prize, the Millennium Technology Grand Prize, the Marcel Benoist Prize, the King Faisal International Science Prize, the Einstein World Award of Science and the Balzan Prize. He is a Fellow of several learned societies and holds eleven honorary doctor’s degrees from European and Asian Universities. His over 1500 publications have received some 220’000 citations with an h-factor of 218 (SI-Web of Science) demonstrating the strong impact of his scientific work.
Pierre DillenbourgAncien instituteur primaire, Pierre Dillenbourg obtient un master en Sciences de lEducation (Université de Mons, Belgique). Dans son projet de master en 1986, il est l'un des premiers au monde à appliquer les méthodes de 'machine learning' à l'éducation, afin de développer un 'self-improving teaching system'. Ceci lui permettra de débuter une thèse de doctorat en informatique à l'Université de Lancaster (UK) dans le domaine des applications éducatives de lintelligence artificielle. Il a été Maître dEnseignement et de Recherche à lUniversité de Genève. Il rejoint l'EPFL en 2012, où Il fut le directeur du Centre de Recherche sur l'Apprentissage, la formation et ses technologies(CRAFT), puis académique du Centre pour l'Education à l'Ere Digitale (CEDE) qui met en oeuvre la stratégie MOOC de l'EPFL (plus de 2 millions d'inscriptions). Il est actuellement professeur ordinaire en technologies de formation aux sein de la faculté Informatique et Communications et dirige laboratoire d'ergonomie éducative (CHILI). Depuis 2006, il a aussi été le directeur de DUAL-T, la 'leading house' dédiée aux technologies pour les systèmes de formation professionnelle duale. Il a fondé plusieurs start-ups dans l'éducation et rejoint plusieurs conseils d'administration. En 2017, Il a créé avec des collègues le 'Swiss EdTech Collider', un incubateur qui rassemble 80 start-ups dans le domaine des technologies éducatives. En 2018, ils ont lancé LEARN, le centre EPFL pour les sciences de l'apprentissage, lequel regroupe les initiatives locales en innovation éducative. Pierre est un 'inaugural fellow of the International Society of Learning Sciences'. Il est actuellement le Vice-Président Associé pour l'Education à l'EPFL.
Patrick ThiranPatrick Thiran is a full professor in network and systems theory at the School of Computer and Communication Sciences at EPFL. He holds an electrical engineering degree from the Université Catholique de Louvain, Louvain-la-Neuve, Belgium, an M.Sc. degree in electrical engineering from the University of California at Berkeley, USA, and he received the PhD degree from EPFL, in 1996. He became an adjunct professor in 1998, an assistant professor in 2002, an associate professor in 2006 and a full professor in 2011. He was with Sprint Advanced Technology Labs in Burlingame, California, in 2000-01.
His research interests are in communication and social networks, performance analysis and stochastic models. He is currently active in the analysis and design of wireless and PLC networks (scaling laws, medium access control), in network monitoring (network tomography, multi-layer networks), and data-driven network science. He also contributed to network calculus and to the theory of locally coupled neural networks and self-organizing maps.
He served as an associate editor for the IEEE Transactions on Circuits and Systems in 1997-99 and for the IEEE/ACM Transactions on Networking in 2006-10. He is currently on the editorial board of the IEEE Journal on Selected Areas in Communication. He is/was on the program committee of different conferences in networking, including ACM Sigcomm, Sigmetrics, IMC, CoNext and IEEE Infocom. He was TPC chair of AMC IMC 2011 and CoNext 2012. He is a Fellow of the Belgian American Educational Foundation and of the IEEE. He received the 1996 EPFL Doctoral Prize and the 2008 Crédit Suisse Teaching Award.
Dominique PiolettiDominique Pioletti received his Master in Physics from the Swiss Federal Institute of Technology Lausanne (EPFL) in 1992. He pursued his education in the same Institution and obtained his PhD in biomechanics in 1997. He developed original constitutive laws taking into account viscoelasticity in large deformations. Then he spent two years at UCSD as post-doc fellow acquiring know-how in cell and molecular biology. He was interested in particular to gene expression of bone cells in contact to orthopedic implant. In April 2006, Dominique Pioletti was appointed Assistant Professor tenure-track at the EPFL and is director of the Laboratory of Biomechanical Orthopedics. His research topics include biomechanics and tissue engineering of musculo-skeletal tissues; mechano-transduction in bone; development of orthopedic implant as drug delivery system. Since 2013, he has been promoted to the rank of Associate Professor.
Alexandre TerrierEnseignement et PhD Doctorant·es actuel·les Mi-Lane Bouchez, Léa Pistorius A co-dirigé les thèses EPFL de Miguel Gortchacow, Adeliya Latypova, Christoph Anselm Engelhardt, Valérie Malfroy Camine, Yasmine Boulanaache, Pezhman Eghbalishamsabadi Cours Engineering of musculoskeletal system and rehabilitation BIO-687 Numerical methods in biomechanics ME-484 Les étudiants comprennent et appliquent les méthodes numériques (MEF) pour répondre à une question de recherche en biomécan
Petr MotlicekEnseignement et PhD Doctorant·es actuel·les Shashi Kumar A co-dirigé les thèses EPFL de Subhadeep Dey, Weipeng He, Juan Pablo Zuluaga Gomez Cours Digital Speech and Audio Coding EE-719 The goal of this course is to introduce the engineering students state-of-the-art speech and audio coding techniques with an emphasis on the integration of knowledge about sound production and auditory perception through signal processing techniques.
Lenka ZdeborováLenka Zdeborová is a Professor of Physics and of Computer Science in École Polytechnique Fédérale de Lausanne where she leads the Statistical Physics of Computation Laboratory. She received a PhD in physics from University Paris-Sud and from Charles University in Prague in 2008. She spent two years in the Los Alamos National Laboratory as the Director's Postdoctoral Fellow. Between 2010 and 2020 she was a researcher at CNRS working in the Institute of Theoretical Physics in CEA Saclay, France. In 2014, she was awarded the CNRS bronze medal, in 2016 Philippe Meyer prize in theoretical physics and an ERC Starting Grant, in 2018 the Irène Joliot-Curie prize, in 2021 the Gibbs lectureship of AMS. She is an editorial board member for Journal of Physics A, Physical Review E, Physical Review X, SIMODS, Machine Learning: Science and Technology, and Information and Inference. Lenka's expertise is in applications of concepts from statistical physics, such as advanced mean field methods, replica method and related message-passing algorithms, to problems in machine learning, signal processing, inference and optimization. She enjoys erasing the boundaries between theoretical physics, mathematics and computer science.
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'
