Pascal FrossardTeaching & PhD PhD Students Yiming Qin, Alba Carballo Castro, Elisa Messori, Ke Wang, Sevda Ögüt, Tuna Alikasifoglu, William Cappelletti, Manuel Madeira, Mahdi Amiri, Ortal Yona Senouf, Vasiliki Rizou, Cem Bilaloglu, Abdellah Rahmani, Amel Abdelraheem, Jérémy Jean Philippe Baffou, Adam Hazimeh, Vincent Jung, Yike Zhao Past EPFL PhD Students Dan Jurca, Jean-Paul Wagner, Ivana Radulovic, Ivana Tosic, Effrosyni Kokiopoulou, Zafer Arican, Vijayaraghavan Thirumalai, Tamara Tosic, Eirina Bourtsoulatze, Elif Vur
Frédéric Jean-Michel AviolatEnseignement et PhD Cours Introduction to data driven business analytics MGT-302 Le cours se concentre sur les méthodes et les algorithmes nécessaires à l'application de l'apprentissage automatique, en mettant l'accent sur les applications dans le domaine de l'analyse commerciale.
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).
Michael Stefan Daniel LieblingEnseignement et PhD A co-dirigé les thèses EPFL de Christian Jaques, Olivia Mariani, Adrian Shajkofci, François Thierry M Marelli Cours Apprentissage et intelligence artificielle EE-311 Ce cours présente une vue générale des techniques d'apprentissage automatique, passant en revue les algorithmes, le formalisme théorique et les protocoles expérimentaux.
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.
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
Michail VlachosEnseignement et PhD Cours Data science and machine learning MGT-502 Introduction pratique à la science des données et à l'apprentissage automatique. Nous abordons les systèmes de recommandation, l'IA générative, les chatbots, les graphes, ainsi que la régression, la classification, l'analyse de texte et les réseaux neuronaux. Programmation en Python.
Emmanuel AbbéMission
Chair of Mathematical Data Science (SB/IC)The research in the chair of Mathematical Data Science (MDS) focuses on the mathematical principles that underpin the analysis and design of information and data science technologies. As branches of mathematics, this involves probability, statistics, and discrete mathematics, and as specific fields, machine learning and information theory. Please consult http://deepfoundations.ai/ for postdoc applications.
Emmanuel Abbe received his Ph.D. degree from the EEC Touradj EbrahimiTouradj EBRAHIMI received his M.Sc. and Ph.D., both in Electrical Engineering, from the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in 1989 and 1992 respectively. In 1993, he was a research engineer at the Corporate Research Laboratories of Sony Corporation in Tokyo, where he conducted research on advanced video compression techniques for storage applications. In 1994, he served as a research consultant at AT&T Bell Laboratories working on very low bitrate video coding. He is currently Professor at EPFL heading its Multimedia Signal Processing Group. He is also the Convenor of JPEG standardization Committee. He was also adjunct Professor with the Center of Quantifiable Quality of Service at Norwegian University of Science and Technology (NTNU)between 2008 and 2012.
Prof. Ebrahimi has been the recipient of various distinctions and awards, such as the IEEE and Swiss national ASE award, the SNF-PROFILE grant for advanced researchers, Four ISO-Certificates for key contributions to MPEG-4 and JPEG 2000, and the best paper award of IEEE Trans. on Consumer Electronics . He became a Fellow of the international society for optical engineering (SPIE) in 2003. Prof. Ebrahimi has initiated more than two dozen National, European and International cooperation projects with leading companies and research institutes around the world. He is a co-founder of Genista SA, a high-tech start-up company in the field of multimedia quality metrics. In 2002, he founded Emitall SA, start-up active in the area of media security and surveillance. In 2005, he founded EMITALL Surveillance SA, a start-up active in the field of privacy and protection. He is or has been associate Editor with various IEEE, SPIE, and EURASIP journals, such as IEEE Signal Processing Magazine, IEEE Trans. on Image Processing, IEEE Trans. on Multimedia, EURASIP Image Communication Journal, EURASIP Journal of Applied Signal Processing, SPIE Optical Engineering Magazine. Prof. Ebrahimi is a member of Scientific Advisory Board of various start-up and established companies in the general field of Information Technology. He has served as Scientific Expert and Evaluator for Research Funding Agencies such as those of European Commission, The Greek Ministry of Development, The Austrian National Foundation for Scientific Research, The Portuguese Science Foundation, as well as a number of Venture Capital Companies active in the field of Information Technologies and Communication Systems. His research interests include still, moving, and 3D image processing and coding, visual information security (rights protection, watermarking, authentication, data integrity, steganography), new media, and human computer interfaces (smart vision, brain computer interface).
He is the author or the co-author of more than 200 research publications, and holds 14 patents. Prof. Ebrahimi is a member of IEEE, SPIE, ACM and IS&T.
See the URL below for more details:
http://mmspl.epfl.ch 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.
André AnjosExpertise
Recherche ReproductibleReconnaissance de FormesTraitement d'ImagesApprentissage AutomatiqueBiométrie
Enseignement et PhD Doctorant·es actuel·les Gökhan Özbulak
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,
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,
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'
Olivier CanévetEnseignement et PhD Cours Machine Learning for Engineers EE-613
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
Amir Roshan ZamirAmir Zamir is a Tenure-Track Assistant Professor of Computer Science at the Swiss Federal Institute of Technology in Lausanne (EPFL). Prior to EPFL, he spent time at Stanford, UC Berkeley, and UCF. His research interests are broadly in computer vision, machine learning, perception-for-robotics, and AI. He has been recognized with CVPR (2018) Best Paper Award, CVPR (2016) Best Student Paper Award, CVPR (2020) Best Paper Award Nomination, and NVIDIA Pioneering Research Award (2018), among others. His research has been covered by various press outlets, such as The New York Times or Forbes.
Myrto LimniosExpertise
Nonparametric statistics, statistical learning theory and methods, stochastic processes
Enseignement et PhD Cours Empirical processes MATH-522 Nous étudierons comment contrôler le comportement non-asymptotique et aléatoire de collections d'estimateurs, lorsqu'indexées par des classes de fonctions/d'ensembles. Des exemples en statistiques et des méthodes non-paramétriques en apprentissage automatique seront traités. Regression methods MATH-408 Cours de niveau master
Maria BrbicMaria Brbic is an assistant professor in computer science at EPFL. Prior to joining EPFL, Maria was a postdoctoral researcher in Computer Science at Stanford University working with Jure Leskovec. She received her PhD degree from University of Zagreb in 2019, while also researching at Stanford University and University of Tokyo. Her research was awarded with the Fulbright Scholarship, L’Oreal UNESCO for Women in Science Scholarship, Branimir Jernej award for outstanding publication in biology and biomedicine, and Josip Loncar Silver Plaque award for the best doctoral dissertation. She has been named a Rising Star in EECS by MIT in 2021. Her research is focused on developing new machine learning methods and applying her methods to advance biomedical research.
