Personnes associées (34)
Pierre Dillenbourg
Ancien instituteur primaire, Pierre Dillenbourg obtient un master en Sciences de l’Education (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 d’Enseignement 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.
Michel Bierlaire
Born in 1967, Michel Bierlaire holds a PhD in Mathematical Sciences from the Facultés Universitaires Notre-Dame de la Paix, Namur, Belgium (University of Namur). Between 1995 and 1998, he was research associate and project manager at the Intelligent Transportation Systems Program of the Massachusetts Institute of Technology (Cambridge, Ma, USA). Between 1998 and 2006, he was a junior faculty in the Operations Research group ROSO within the Institute of Mathematics at EPFL. In 2006, he was appointed associate professor in the School of Architecture, Civil and Environmental Engineering at EPFL, where he became the director of the Transport and Mobility laboratory. Since 2009, he is the director of TraCE, the Transportation Center. From 2009 to 2017, he was the director of Doctoral Program in Civil and Environmental Engineering at EPFL. In 2012, he was appointed full professor at EPFL. Since September 2017, he is the head of the Civil Engineering Institute at EPFL.   His main expertise is in the design, development and applications of models and algorithms for the design, analysis and management of transportation systems. Namely, he has been active in demand modeling (discrete choice models, estimation of origin-destination matrices), operations research (scheduling, assignment, etc.) and Dynamic Traffic Management Systems.  As of August 2021, he has published 136 papers in international journals, 4 books, 41 book chapters, 193 articles in conference proceedings, 182 technical reports, and has given 195 scientific seminars. His Google Scholar h-index is 68.  He is the founder, organizer and lecturer of the EPFL Advanced Continuing Education Course "Discrete Choice Analysis: Predicting Demand and Market Shares".   He is the founder of hEART: the European Association for Research in Transportation.   He was the founding Editor-in-Chief of the EURO Journal on Transportation and Logistics, from 2011 to 2019. He is an Associate Editor of Operations Research. He is the editor of two special issues for the journal Transportation Research Part C. He has been member of the Editorial Advisory Board (EAB) of Transportation Research Part B since 1995, of Transportation Research Part C since January 1, 2006.
Denis Gillet
Denis Gillet received the Diploma in Electrical Engineering from the Swiss Federal Institute of Technology in Lausanne (EPFL) in 1988, and the Ph.D. degree in Information Systems also from the EPFL in 1995. During 1992 he was appointed as Research Fellow at the Information Systems Laboratory of Stanford University in the United States. He is currently Maître d'enseignement et de recherche at the EPFL School of Engineering, where he leads the React research group. His current research interests include Technologies Enhanced Learning (TEL), Human Computer Interaction (HCI), Human Devices Interaction (HDI) and Optimal Coordination of Complex and Distributed Systems. Denis Gillet is affiliated at EPFL with the Center for Intelligent Systems and the Center for Digital Education.
Lijing Xin
Lijing Xin is a research staff scientist and 7T MR Operational Manager at the Center for Biomedical Imaging (CIBM), Ecole polytechnique fédérale de Lausanne (EPFL), Switzerland. Her research interests focus on developing cutting-edge magnetic resonance spectroscopy and imaging methods for better understanding the brain function and the pathophysiology of neurological diseases. Her journey on magnetic resonance imaging (MRI) started from her master project during 2002-2005, where she developed a gradient unit with eddy current compensation and a pulse sequence generator for MRI spectrometer, which enhanced her knowledge in MR instrumentation. Later, she obtained her PhD in physics from Ecole polytechnique fédérale de Lausanne (EPFL) in 2010, where she focused on developing various novel 1H and 13C magnetic resonance spectroscopy (MRS) acquisition and quantification methods as well as RF coils on high field preclinical MR scanners. Afterwards, she started working on the clinical MR platforms including both 3 and 7T and continued to improve and develop novel acquisition and quantification methods for 1H, 13C and 31P nuclei. She carries on interdisciplinary collaborations with different partners, particularly with clinical partners where translational strategies are performed to explore the pathophysiology of psychiatric disorders and disease biomarkers for early diagnose and intervention.
Johan Auwerx
Johan Auwerx is Professor at the École Polytechnique Fédérale in Lausanne, Switzerland, where he occupies the Nestle Chair in Energy Metabolism. Dr. Auwerx has been using molecular physiology and systems genetics to understand metabolism in health, aging and disease. Much of his work focused on understanding how diet, exercise and hormones control metabolism through changing the expression of genes by altering the activity of transcription factors and their associated cofactors. His work was instrumental for the development of agonists of nuclear receptors - a particular class of transcription factors - into drugs, which now are used to treat high blood lipid levels, fatty liver, and type 2 diabetes. Dr. Auwerx was amongst the first to recognize that transcriptional cofactors, which fine-tune the activity of transcription factors, act as energy sensors/effectors that influence metabolic homeostasis. His research validated these cofactors as novel targets to treat metabolic diseases, and spurred the clinical use of natural compounds, such as resveratrol, as modulators of these cofactor pathways. Johan Auwerx was elected as a member of EMBO in 2003 and is the recipient of a dozen of international scientific prizes, including the Danone International Nutrition Award, the Oskar Minkowski Prize, and the Morgagni Gold Medal. His work is highly cited by his peers with a h-factor of over 100. He is an editorial board member of several journals, including Cell Metabolism, Molecular Systems Biology, The EMBO Journal, Journal of Cell Biology, Cell, and Science. Dr. Auwerx co-founded a handful of biotech companies, including Carex, PhytoDia, and most recently Mitobridge, and has served on several scientific advisory boards. Dr. Auwerx received both his MD and PhD in Molecular Endocrinology at the Katholieke Universiteit in Leuven, Belgium. He was a post-doctoral research fellow in the Departments of Medicine and Genetics of the University of Washington in Seattle.

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