Maria del Carmen Sandi PerezACADEMIC POSITION:
Professor, Director of the Laboratory of Behavioral Genetics, Brain Mind Institute, Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland.
EDUCATION:
BS MS Salamanca, Spain, 1984
PhD Cajal Institute, CSIC, and University Autonoma of Madrid, Spain, 1988
PROFESSIONAL EXPERIENCE:
Postdoc at INSERM, Bordeaux, France, and Cajal Institute Madrid, Spain, 1989-1990
Postdoc at the Open University, UK, 1991-1992, 1996
Research Associate, Cajal Institute, CSIC, Madrid, 1993-1995
Associate Professor Tenured, UNED University, Madrid, 1996-2003
Sabbatical Professor, University of Bern, Switzerland, 2002-2003
Assistant Professor Tenure-Track, EPFL, 2003-2007
Associate Professor Tenured, EPFL, 2007-2012
Full Professor, EPFL, 2012-
Director, Brain Mind Institute, EPFL, 2012-
PRINCIPAL BOARDS:
President, European Brain and Behavior Society (EBBS), 2009-2012
Editor-in-Chief Frontiers in Behavioral Neuroscience
Member of Scientific Advisory Panel, European College Neuropsychopharmacology (ECNP)
Member of the European Dana Alliance for the Brain (EDAB)
Associate Editor Frontiers in Neuroscience
Editorial Board Member Neurobiology of Learning and Memory
Editorial Board Member Journal of Psychiatry Research
Editorial Board Member Stress
Editorial Board Member Biology of Mood and Anxiety Disorders
Editorial Board Member Neuroscience and Biobehavioral Reviews
Claudia Rebeca Binder SignerNée à Montréal, Claudia R. Binder est d’origine canadienne, suisse et colombienne. Elle grandit entre la Suisse et la Colombie. Alumni de l’ETH de Zurich, elle y obtient un diplôme en biochimie et un doctorat en Sciences de l'environnement, de 1985 à 1996. Elle poursuit sa carrière avec un post doctorat à l'Université du Maryland, aux États-Unis, de 1996 à 1998, et travaille en qualité d’assistante-senior à l’ETH jusqu’en 2006, où elle se spécialise dans les systèmes humains-environnementaux. Elle est ensuite nommée Professeure assistante au Département de géographie de l'Université de Zurich, un poste qu’elle occupe jusqu’en 2009.
Elle obtient en 2009 le titre de Professeure ordinaire en Sciences systémiques à l’Université de Graz, en Autriche et rejoint en 2011 le Département de Géographie de l’Université de Munich, en Allemagne, en tant que Professeure ordinaire en relations humaines-environnementales. Elle intègre l’EPFL en mars 2016, où elle ouvre le Laboratoire de relations humaines-environnementales dans les systèmes urbains (HERUS), rattaché à la Chaire La Mobilière pour l’écologie urbaine et un mode de vie durable, au sein de la Faculté de l’environnement naturel, architectural et construit (ENAC).
Ses recherches portent sur l'analyse, la modélisation et l'évaluation de la transition des systèmes urbains vers la durabilité. Elle examine en particulier comment nous pouvons mieux comprendre la dynamique du métabolisme urbain, ce qui caractérise une ville durable et ce qui anime et entrave les processus de transformation. Elle explore ces sujets en combinant les domaines des sciences sociales, des sciences naturelles et de la science des données. Ses recherches portent sur l'alimentation, l'énergie, les modes de vie et les transports durables dans les systèmes urbains.
En Suisse, Binder a été nommé membre du Conseil de la recherche, Division des programmes du Fonds national suisse (FNS) en 2016 et fait partie du Comité directeur du Programme national de recherche 71 du FNS, "Gestion de la consommation d'énergie" et du Swiss Competence Centers for Energy Research (SCCER). Elle est également membre du comité directeur sur Sustainability Research des Académies suisses des sciences et des lettres. En 2019, elle a été élue membre du Conseil universitaire de l'Université de Munich (LMU).
A l’EPFL, Claudia R. Binder est la directrice académique du programme d’enseignement interdisciplinaire «Projeter Ensemble». Elle a été nommée membre de la Direction du Centre de l'énergie en 2018 et dirige depuis 2019 le groupe de travail sur la Stratégie énergétique et de durabilité de l’école.
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.
Dario FloreanoProf. Dario Floreano is director of the Laboratory of Intelligent Systems at the Swiss Federal Institute of Technology Lausanne (EPFL). Since 2010, he is the founding director of the Swiss National Center of Competence in Robotics, a research program that brings together more than 20 labs across Switzerland. Prof. Floreano holds an M.A. in Vision, an M.S. in Neural Computation, and a PhD in Robotics. He has held research positions at Sony Computer Science Laboratory, at Caltech/JPL, and at Harvard University. His main research interests are Robotics and A.I. at the convergence of biology and engineering. Prof. Floreano made pioneering contributions to the fields of evolutionary robotics, aerial robotics, and soft robotics. He served in numerous advisory boards and committees, including the Future and Emerging Technologies division of the European Commission, the World Economic Forum Agenda Council, the International Society of Artificial Life, the International Neural Network Society, and in the editorial committee of several scientific journals. In addition, he helped spinning off two drone companies (senseFly.com and Flyability.com) and a non-for-profit portal on robotics and A.I. (RoboHub.org). Books
Manuale sulle Reti Neurali, il Mulino (in Italian), 1996 (first edition), 2006 (second edition)Evolutionary Robotics, MIT Press, 2000
Bio-Inspired Artificial Intelligence, MIT Press, 2008
Flying Insects and Robots, Springer Verlag, 2010
Michel BierlaireBorn 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.
Daniel ThalmannProf. Daniel Thalmann is Honorary Professor at EPFL and Director of Research development at MIRALab Sarl. He has been Visiting Professor at The Institute for Media Innovation (Nanyang Technological University, Singapore) from 2009 to 2017. He is a pioneer in research on Virtual Humans. His current research interests include Real-time Virtual Humans in Virtual Reality, crowd simulation, and 3D Interaction. Daniel Thalmann has been the Founder of The Virtual Reality Lab (VRlab) at EPFL, Switzerland, Professor at The University of Montreal and Visiting Professor/ Researcher at CERN, University of Nebraska, University of Tokyo, and National University of Singapore. Until October 2010, he was the President of the Swiss Association of Research in Information Technology and one Director of the European Research Consortium in Informatics and Mathematics (ERCIM). He is coeditor-in-chief of the Journal of Computer Animation and Virtual Worlds, and member of the editorial board of 6 other journals. Daniel Thalmann was member of numerous Program Committees, Program Chair and CoChair of several conferences including IEEE VR, ACM VRST, and ACM VRCAI. Daniel Thalmann has published more than 500 papers in Graphics, Animation, and Virtual Reality. He is coeditor of 30 books, and coauthor of several books including 'Crowd Simulation' (second edition 2012) and 'Stepping Into Virtual Reality' (2007), published by Springer. He received his PhD in Computer Science in 1977 from the University of Geneva and an Honorary Doctorate (Honoris Causa) from University Paul- Sabatier in Toulouse, France, in 2003. He also received the Eurographics Distinguished Career Award in 2010 and the 2012 Canadian Human Computer Communications Society Achievement Award. Wikipedia: http://en.wikipedia.org/wiki/Daniel_Thalmann Henry MarkramHenry Markram started a dual scientific and medical career at the University of Cape Town, in South Africa. His scientific work in the 80s revealed the polymodal receptive fields of pontomedullary reticular formation neurons in vivo and how acetylcholine re-organized these sensory maps.
He moved to Israel in 1988 and obtained his PhD at the Weizmann Institute where he discovered a link between acetylcholine and memory mechanisms by being the first to show that acetylcholine modulates the NMDA receptor in vitro studies, and thereby gates which synapses can undergo synaptic plasticity. He was also the first to characterize the electrical and anatomical properties of the cholinergic neurons in the medial septum diagonal band.
He carried out a first postdoctoral study as a Fulbright Scholar at the NIH, on the biophysics of ion channels on synaptic vesicles using sub-fractionation methods to isolate synaptic vesicles and patch-clamp recordings to characterize the ion channels. He carried out a second postdoctoral study at the Max Planck Institute, as a Minerva Fellow, where he discovered that individual action potentials propagating back into dendrites also cause pulsed influx of Ca2 into the dendrites and found that sub-threshold activity could also activated a low threshold Ca2 channel. He developed a model to show how different types of electrical activities can divert Ca2 to activate different intracellular targets depending on the speed of Ca2 influx an insight that helps explain how Ca2 acts as a universal second messenger. His most well known discovery is that of the millisecond watershed to judge the relevance of communication between neurons marked by the back-propagating action potential. This phenomenon is now called Spike Timing Dependent Plasticity (STDP), which many laboratories around the world have subsequently found in multiple brain regions and many theoreticians have incorporated as a learning rule. At the Max-Planck he also started exploring the micro-anatomical and physiological principles of the different neurons of the neocortex and of the mono-synaptic connections that they form - the first step towards a systematic reverse engineering of the neocortical microcircuitry to derive the blue prints of the cortical column in a manner that would allow computer model reconstruction.
He received a tenure track position at the Weizmann Institute where he continued the reverse engineering studies and also discovered a number of core principles of the structural and functional organization such as differential signaling onto different neurons, models of dynamic synapses with Misha Tsodyks, the computational functions of dynamic synapses, and how GABAergic neurons map onto interneurons and pyramidal neurons. A major contribution during this period was his discovery of Redistribution of Synaptic Efficacy (RSE), where he showed that co-activation of neurons does not only alter synaptic strength, but also the dynamics of transmission. At the Weizmann, he also found the tabula rasa principle which governs the random structural connectivity between pyramidal neurons and a non-random functional connectivity due to target selection. Markram also developed a novel computation framework with Wolfgang Maass to account for the impact of multiple time constants in neurons and synapses on information processing called liquid computing or high entropy computing.
In 2002, he was appointed Full professor at the EPFL where he founded and directed the Brain Mind Institute. During this time Markram continued his reverse engineering approaches and developed a series of new technologies to allow large-scale multi-neuron patch-clamp studies. Markrams lab discovered a novel microcircuit plasticity phenomenon where connections are formed and eliminated in a Darwinian manner as apposed to where synapses are strengthening or weakened as found for LTP. This was the first demonstration that neural circuits are constantly being re-wired and excitation can boost the rate of re-wiring.
At the EPFL he also completed the much of the reverse engineering studies on the neocortical microcircuitry, revealing deeper insight into the circuit design and built databases of the blue-print of the cortical column. In 2005 he used these databases to launched the Blue Brain Project. The BBP used IBMs most advanced supercomputers to reconstruct a detailed computer model of the neocortical column composed of 10000 neurons, more than 340 different types of neurons distributed according to a layer-based recipe of composition and interconnected with 30 million synapses (6 different types) according to synaptic mapping recipes. The Blue Brain team built dozens of applications that now allow automated reconstruction, simulation, visualization, analysis and calibration of detailed microcircuits. This Proof of Concept completed, Markrams lab has now set the agenda towards whole brain and molecular modeling.
With an in depth understanding of the neocortical microcircuit, Markram set a path to determine how the neocortex changes in Autism. He found hyper-reactivity due to hyper-connectivity in the circuitry and hyper-plasticity due to hyper-NMDA expression. Similar findings in the Amygdala together with behavioral evidence that the animal model of autism expressed hyper-fear led to the novel theory of Autism called the Intense World Syndrome proposed by Henry and Kamila Markram. The Intense World Syndrome claims that the brain of an Autist is hyper-sensitive and hyper-plastic which renders the world painfully intense and the brain overly autonomous. The theory is acquiring rapid recognition and many new studies have extended the findings to other brain regions and to other models of autism.
Markram aims to eventually build detailed computer models of brains of mammals to pioneer simulation-based research in the neuroscience which could serve to aggregate, integrate, unify and validate our knowledge of the brain and to use such a facility as a new tool to explore the emergence of intelligence and higher cognitive functions in the brain, and explore hypotheses of diseases as well as treatments.
Katrin BeyerSince 2017 Associate Professor, School of Architecture, Civil and Environmental Engineering (ENAC), EPFL. Head of the Earthquake Engineering and Structural Dynamics (EESD) Laboratory
2010-2017 Assistant Professor, EPFL.
2008-2010 Post-doctoral researcher, ETH Zürich.
2003-2007 Ph.D., Roseschool / Università di Pavia, Italy.
2001-2003 Ove Arup & Partners, Advanced Technology and Research Group, London.
2001 Diploma, Civil engineering, ETH Zürich.
Wulfram GerstnerWulfram Gerstner is Director of the Laboratory of Computational Neuroscience LCN at the EPFL. His research in computational neuroscience concentrates on models of spiking neurons and spike-timing dependent plasticity, on the problem of neuronal coding in single neurons and populations, as well as on the link between biologically plausible learning rules and behavioral manifestations of learning. He teaches courses for Physicists, Computer Scientists, Mathematicians, and Life Scientists at the EPFL. After studies of Physics in Tübingen and at the Ludwig-Maximilians-University Munich (Master 1989), Wulfram Gerstner spent a year as a visiting researcher in Berkeley. He received his PhD in theoretical physics from the Technical University Munich in 1993 with a thesis on associative memory and dynamics in networks of spiking neurons. After short postdoctoral stays at Brandeis University and the Technical University of Munich, he joined the EPFL in 1996 as assistant professor. Promoted to Associate Professor with tenure in February 2001, he is since August 2006 a full professor with double appointment in the School of Computer and Communication Sciences and the School of Life Sciences. Wulfram Gerstner has been invited speaker at numerous international conferences and workshops. He has served on the editorial board of the Journal of Neuroscience, Network: Computation in Neural Systems', Journal of Computational Neuroscience', and `Science'.
Ali H. SayedAli H. Sayed est doyen de la Faculté des sciences et techniques de l’ingénieur (STI) de l'EPFL, en Suisse, où il dirige également le laboratoire de systèmes adaptatifs. Il a également été professeur émérite et président du département d'ingénierie électrique de l'UCLA. Il est reconnu comme un chercheur hautement cité et est membre de la US National Academy of Engineering. Il est également membre de l'Académie mondiale des sciences et a été président de l'IEEE Signal Processing Society en 2018 et 2019.
Le professeur Sayed est auteur et co-auteur de plus de 570 publications et de six monographies. Ses recherches portent sur plusieurs domaines, dont les théories d'adaptation et d'apprentissage, les sciences des données et des réseaux, l'inférence statistique et les systèmes multi-agents, entre autres.
Ses travaux ont été récompensés par plusieurs prix importants, notamment le prix Fourier de l'IEEE (2022), le prix de la société Norbert Wiener (2020) et le prix de l'éducation (2015) de la société de traitement des signaux de l'IEEE, le prix Papoulis (2014) de l'Association européenne de traitement des signaux, le Meritorious Service Award (2013) et le prix de la réalisation technique (2012) de la société de traitement des signaux de l'IEEE, le prix Terman (2005) de la société américaine de formation des ingénieurs, le prix de conférencier émérite (2005) de la société de traitement des signaux de l'IEEE, le prix Koweït (2003) et le prix Donald G. Fink (1996) de l'IEEE. Ses publications ont été récompensées par plusieurs prix du meilleur article de l'IEEE (2002, 2005, 2012, 2014) et de l'EURASIP (2015). Pour finir, Ali H. Sayed est aussi membre de l'IEEE, d'EURASIP et de l'American Association for the Advancement of Science (AAAS), l'éditeur de la revue Science.
Auke IjspeertAuke Ijspeert is a full professor at the EPFL, and head of the Biorobotics Laboratory (BioRob). He has a B.Sc./M.Sc. in physics from the EPFL (1995), and a PhD in artificial intelligence from the University of Edinburgh (1999). He carried out postdocs at IDSIA and EPFL, and at the University of Southern California (USC). He then became a research assistant professor at USC, and an external collaborator at ATR (Advanced Telecommunications Research institute) in Japan. In 2002, he came back to the EPFL as an SNF assistant professor. He was promoted to associate professor in October 2009 and to full professor in April 2016. His primary affiliation is with the Institute of Bioengineering, and secondary affiliation with the Institute of Mechanical Engineering. His research interests are at the intersection between robotics, computational neuroscience, nonlinear dynamical systems, and machine learning. He is interested in using numerical simulations and robots to get a better understanding of sensorimotor coordination in animals, and in using inspiration from biology to design novel types of robots and adaptive controllers. (see for instance Ijspeert et al Science 2007, Ijspeert Science 2014, and Nyakatura et al Nature 2019). He is also investigating how to assist people with limited mobility using exoskeletons and assistive furniture. He is regularly invited to give talks on these topics (e.g. TED talk given at TED Global Geneva, Dec 8 2015). With his colleagues, he has received paper awards at ICRA2002, CLAWAR2005, IEEE Humanoids 2007, IEEE ROMAN 2014, CLAWAR 2015, SAB2018, and CLAWAR 2019. He is an IEEE Fellow, member of the Board of Reviewing Editors of Science magazine, and associate editor for the IEEE Transactions on Medical Robotics and Bionics and for the International Journal of Humanoid Robotics. He has acted as an associate editor for the IEEE Transactions on Robotics (2009-2013) and for Soft Robotics (2018-2021). He was a guest editor for the Proceedings of IEEE, IEEE Transactions on Biomedical Engineering, Autonomous Robots, IEEE Robotics and Automation Magazine, and Biological Cybernetics. He has been the organizer of 7 international conferences (BioADIT2004, SAB2004, AMAM2005, BioADIT2006, LATSIS2006, SSRR2016, AMAM2019), and a program committee member of over 50 conferences.
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.
