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.
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.
Alexandre Massoud AlahiAlexandre Alahi is currently an Assistant Professor at EPFL. He spent five years at Stanford University as a Post-doc and Research Scientist after obtaining his Ph.D. from EPFL. His research enables machines to perceive the world and make decisions in the context of transportation problems and smart environments. He has worked on the theoretical challenges and practical applications of socially-aware Artificial Intelligence, i.e., systems equipped with perception and social intelligence. He was awarded the Swiss NSF early and advanced researcher grants for his work on predicting human social behavior. He won the CVPR Open Source Award (2012) for his work on Retina-inspired image descriptors, and the ICDSC Challenge Prize (2009) for his sparsity-driven algorithm that has tracked more than 100 million pedestrians to date. His research has been covered internationally by BBC, abc, PBS, Euronews, Wall street journal, and other national news outlets around the world. Alexandre has also co-founded multiple startups such as Visiosafe, and won several startup competitions. He was elected as one of the Top 20 Swiss Venture leaders in 2010.
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.
Olivier VerscheureEnseignement et PhD Cours Data science pour ingénieurs avec Python ENG-209 Ce cours propose une immersion progressive et complète dans le domaine de la Data Science à travers le langage Python. Il guide les étudiants depuis la manipulation de données brutes jusqu'à la modélisation et l'extraction de connaissances utiles à partir de données réelles. Large-scale data science for real-world data COM-490 Ce cours pratique couvre outils et méthodes des data scientists, de la reche
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).
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.
Jean-Louis ScartezziniDirecteur du Laboratoire d'Energie Solaire et de Physique du Bâtiment à l'EPFL (1994-présent); Fondateur & Directeur de l'Institut des Infrastructures, des Ressources et de l'Environnement à l'ENAC (2002-2009); Fondateur & Directeur du Programme Doctoral en Environnement de l'EPFL (2002-2009); Co-Directeur de l'Institut des Techniques du Bâtiment de l'EPFL (1994-1997); Professeur Associé de Physique du Bâtiment à l'EPFL (1994-1997); Professeur Associé de Physique du Bâtiment à l'Université de Genève (1990-1997); Chef de Groupe & Chercheur associé au Laboratoire d'Energie Solaire et de Physique du Bâtiment de l'EPFL (1981-1989); Chercheur associé au Groupe de Recherche en Energie Solaire de l'EPFL (1981-1989); Chercheur associé à l'Institut de Géophysique Appliquée de l'Université de Lausanne (1980-1981).
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,
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.
Mike SeidelEnseignement et PhD Doctorant·es actuel·les Simon Fanica Buijsman, Jesús Avila Pulido, Ingrid Midtbust Hjelle, Maria Paula Rey Barrera, Raziyeh Dadashi Motlagh, Zdenek Vostrel, Evan James Ericson, Yi Wu, Lode Vanhecke, Roberta Provvedi, Adam Mark Furman, Aikaterini Nikou, Felix Höfenstock, Ludovica Bertolozzi, Simone Giroldi A dirigé les thèses EPFL de Marco Hartmann, Péter Kicsiny, Rongrong Cai, André Donadón Servelle, Longdi Zhu, Sofia Carolina Johannesson, Vera Korchevnyuk, Nicolas Vallis, Elias Walter
Tatiana PieloniEnseignement et PhD Doctorant·es actuel·les Yi Wu, Lode Vanhecke A co-dirigé les thèses EPFL de Xavier Buffat, Claudia Tambasco Cours Advanced concepts in particle accelerators PHYS-751 Introduction to particle accelerators PHYS-448 Le cours présente des idées de base de physique des accélérateurs. Nous allons examiner les caractéristiques et les limitations de ces machines utilisés dans les sciences comme la physique des hautes énergies, des matériaux et de la vie.
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.
Ian SmithPhD Université de Cambridge, 1982 Interêts 1 Contrôle actif de la forme des structures pour améliorer leur aptitude au service et leur déploiement 2 Structures biomimétiques (apprentissage, auto-diagnostic, auto-réparation) 3 Gestion de l'infrastructure par l'identification structurale 4 Applications avancées de l'informatique Plus de détails, voir https://www.epfl.ch/labs/imac/fr/recherche/smith_ian_fr/ 