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
Devis TuiaI come from Ticino and studied in Lausanne, between UNIL and EPFL. After my PhD at UNIL in remote sensing, I was postdoc in Valencia (Spain), Boulder (CO) and EPFL, working on model adaptation and prior knowledge integration in machine learning. In 2014 I became Research Assistant Professor at University of Zurich, where I started the 'multimodal remote sensing' group. In 2017, I joined Wageningen University (NL), where I was professor of the GeoInformation Science and Remote Sensing Laboratory. Since 2020, I joined EPFL Valais, to start the ECEO lab, working at the interface between Earth observation, machine learning and environmental sciences.
Murat KuntNé le 16 janvier 1945 à Ankara, a fait sa scolarité au lycée de Galatasaray, l'une des plus vieilles institutions créée en 1481 suivant un accord entre la France et l'Empire Ottomane. Il a reçu son diplôme d'ingénieur-physicien de l'Ecole Polytechnique Fédérale de Lausanne (EPFL) en 1969 et son diplôme de docteur ès sciences en 1974 de la même institution avec une thèse sur la compression de facsimilé.
De 1974 à 1977 il a travaillé au Massachusetts Institute of Technology à Boston comme Research Fellow au Research Laboratory of Electronics.
De retour en Suisse en 1977, il a repris un poste d'Adjoint scientifique au Laboratoire de traitement des signaux à l'Ecole Polytechnique Fédérale de Lausanne (EPFL). Il a travaillé sur la compression des images et de la vidéo, les signaux biomédicaux et la vision par ordinateur.
En 1978 il a créé la revue scientifique Signal Processing dont il est le rédacteur en chef et l'Association européenne de traitement des signaux (EURASIP).
Il a été nommé professeur en 1980
Dès 1986, il reçoit des mandats importants (8 Mio Fr.suisses chacun) de groupes industriels comme Thomson CSF et Hewlett-Packard.
En 1987 il a été nommé rapporteur à l'Assemblée National française (MM. Raymod Forni et Michel Pelcha, députés) pour la télévion à haute définition.
En 1989 il a été nommé directeur du Laboratoire de traitement des signaux.
Jusqu'à maintenant, il a :
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dirigé plus 60 thèses de doctorats à l'EPFL
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participé au jury de plus de 100 thèses dans les universités européennes
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été invité à donner de plus 250 conférences à travers le monde
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publié de plus 250 articles et 14 livres
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présidé 5 conférences internationales
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participé à plus de 30 projets européens comme partenaire
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reçu le médaille de services méritoires de l'EURASIP en 1983.
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reçu la distinction de Fellow IEEE en 1986
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reçu le prix de « Technical Achievement » de IEEE - The Institute of Electrical and Electronics Engineers - en 1997
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reçu le médaille du 3ème millénaire de IEEE - The Institute of Electrical and Electronics Engineers - en 2000
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reçu le doctorat honoris causa de l'Université Catholique de Louvain en 2001
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reçu le prix de « Technical Achievement » d'EURASIP en 2003
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reçu le prix « scientifique en imagerie de l'année » de IS&T et SPIE en 2003.
En 2007 il a crée une nouvelle revue scientifique Signal, Image and Video Processing dont il assume la direction, chez Springer. Il a pris sa retraite en juin 2008 et a été nommé Professeur honoraire.
Voir le site http://lts5www.epfl.ch/kunt.html pour plus de détail. 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.
Olga FinkEnseignement et PhD Doctorant·es actuel·les Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei A dirigé les thèses EPFL de Ismail Nejjar, Mengjie Zhao Cours Data Science for infrastructure condition monitoring CIVIL-332 Le cours couvrira les étapes pertinentes de la surveillance de l'état des infrastructures basée sur les données: l'acquisition des données, en passant p
Mengjie ZhaoMengjie Zhao holds degrees in Computational Mechanics (MSc) with honors track and in Engineering Science (BSc) from the Technical University of Munich (TUM).
From the early years of her studies, Mengjie was fascinated by the modeling of multiphysics and multiscale systems. As a student research assistant at TUM and research intern at International Centre for Numerical Methods in Engineering (CIMNE), she gained a solid understanding of both the theoretical and algorithmic fundamentals as well as a wide range of applications. Through the BGCE project with the Elitenetzwerk Bayern (ENB), which dealt with the mesh sensitivity prediction with a deep neural network, she realized that leveraging data could bring physical modeling far beyond the current computational limits. Later, in her master's thesis in cooperation with Siemens, she turned to the reduced-order modeling with enforced physical invariants, which showed better accuracy and generality.
In her Ph.D., she would like to step towards a further combination of deductive research (modeling and simulation) and inductive (data-driven) research by embedding physics into machine learning.
Keivan Faghih NiresiExpertise
Computational sensing/imaging, Inverse problems, Signal processing, Graph neural networks, Domain adaptation.
Keivan is a PhD student at école Polytechnique Fédérale de Lausanne (EPFL). He joined the Intelligent Maintenance and Operations Systems (IMOS) Lab under the supervision of Prof. Olga Fink in February 2023.Prior to joining EPFL, he obtained his master's degree from the Institute of Communications Engineering, College of Electrical Engineering and Computer Science, National Tsing Hua Univer
Mackenzie MathisCenter for NeuroprostheticsEPFL ELLIS Unit Faculty MemberCenter for Intelligent Systems
Alexander MathisAlexander studied pure mathematics with a minor in logic and theory of science at the Ludwig Maximilians University in Munich. For his PhD also at LMU, he worked on optimal coding approaches to elucidate the properties of grid cells. As a postdoctoral fellow with Prof. Venkatesh N. Murthy at Harvard University and Prof. Matthias Bethge at Tuebingen AI, he decided to study olfactory behaviors such as odor-guided navigation, social behaviors and the cocktail party problem in mice. During this time, he increasingly got interested sensorimotor behaviors beyond olfaction and started working on proprioception, motor adaption, as well as computer vision tools for measuring animal behavior.
In his group, he is interested in elucidating how the brain gives rise to adaptive behavior. One of the major goals is to synthesize large datasets into computationally useful information. For those purposes, he develops algorithms and systems to analyze animal behavior (e.g. DeepLabCut), neural data, as well as creates experimentally testable computational models.
Mathieu SalzmannI am a Senior Researcher at EPFL-CVLab, and, since May 2020, an Artificial Intelligence Engineer at ClearSpace (50%). Previously, I was a Senior Researcher and Research Leader in NICTA's computer vision research group. Prior to this, from Sept. 2010 to Jan 2012, I was a Research Assistant Professor at TTI-Chicago, and, from Feb. 2009 to Aug. 2010, a postdoctoral fellow at ICSI and EECS at UC Berkeley under the supervision of Prof. Trevor Darrell. I obtained my PhD in Jan. 2009 from EPFL under the supervision of Prof. Pascal Fua.
