Harald BruneOriginaire de Münich en Allemagne, né en 1961, Harald Brune obtient son diplôme en physique de l'Université Ludwig Maximilians en 1989. Après une thèse en chimie physique à l'Institut Fritz-Haber de la Société Max-Planck à Berlin il obtient son titre de docteur ès sciences en 1992. Dès cela, il rejoint le groupe du Prof. K. Kern à l'Institut de physique expérimentale à l'EPFL. En 1995 il est chercheur invité à Copenhague travaillant en modélisation chez le Prof. J. Nørskov. De retour à l'EPFL, il se voit décerné le prix Latsis EPFL 1996 pour ses études par microscopie à effet tunnel de processus atomiques déterminants la croissance cristalline de couches minces. En 1998 il obtient son habilitation (venia legendi) en Physique et est nommé Maître d'enseignement et de recherche (MER) en nanophysique à l'EPFL. La même année il recoit une offre de Professeur Ordinaire (C4) de l'Université Philipps de Marburg. Début 1999 il réfuse cette offre et accepte un poste de Professeur Extraordinaire à l'EPFL et s'installe au sein de l'Institut de la Physique des Nanostructures. Il est nommé Professeur Ordinaire en 2005. Sa recherche porte sur les propriétés physiques (en particulier le magnétisme et la structure électronique) de nouvelles formes de la matière condensée comme des nanostructures et des couches ultra-minces. Il s'intéresse également à la catalyse hétérogène sur des systèmes inspirés dans leur composition et taille par celle des sites actives dans les enzymes en biologie. Il enseigne la Physique Générale pour ingénieurs, la Physique des matériaux solides pour physiciens, les méthodes expérimentales pour physiciens, ainsi que la Physique des surfaces, interfaces et nanostrcutures à l'école doctorale.
Pierre DillenbourgA former teacher in elementary school, Pierre Dillenbourg graduated in educational science (University of Mons, Belgium). He started his research on learning technologies in 1984. In 1986, he has been on of the first in the world to apply machine learning to develop a self-improving teaching system. He obtained a PhD in computer science from the University of Lancaster (UK), in the domain of artificial intelligence applications for education. He has been assistant professor at the University of Geneva. He joined EPFL in 2002. He has been the director of Center for Research and Support on Learning and its Technologies, then academic director of Center for Digital Education, which implements the MOOC strategy of EPFL (over 2 million registrations). He is full professor in learning technologies in the School of Computer & Communication Sciences, where he is the head of the CHILI Lab: "Computer-Human Interaction for Learning & Instruction ». He is the director of the leading house DUAL-T, which develops technologies for dual vocational education systems (carpenters, florists,...). With EPFL colleagues, he launched in 2017 the Swiss EdTech Collider, an incubator with 80 start-ups in learning technologies. He (co-)-founded 4 start-ups, does consulting missions in the corporate world and joined the board of several companies or institutions. In 2018, he co-founded LEARN, the EPFL Center of Learning Sciences that brings together the local initiatives in educational innovation. He is a fellow of the International Society for Learning Sciences. He currently is the Associate Vice-President for Education at EPFL.
Francesco StellacciFrancesco Stellacci graduated in Materials Engineering at the Politecnico di Milano in 1998 with a thesis on photochromic polymers with Prof. Giuseppe Zerbi and Mariacarla Gallazzi. In 1999 he moved to the Chemistry Department of the University of Arizona for as a post-doc in the group of Joe Perry in close collaboration with the group of Seth Marder. In 2002 he moved to the Department of Materials Science and Engineering at the Massachusetts Institute of Technology as an assistant professor. He was then promoted to associate without (2006) and with tenure (2009). In 2010 he moved to the Institute of Materials at EPFL as a full Professor. He holds the Alcan EP Chair. Francesco was one of the recipients of the Technology Review TR35 "35 Innovator under 35" award in 2005, and the Popular Science Magazine "Brilliant 10" award in 2007. He has been a Packard Fellow starting 2005.
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.
Willy ZwaenepoelWilly Zwaenepoel received his B.S. from the University of Gent, Belgium in 1979, and his M.S. and Ph.D. from Stanford University in 1980 and 1984, respectively. In September 2002, he joined EPFL. He was Dean of the School of Computer and Communications Sciences at EPFL from 2002 to 2011. Before joining EPFL, Willy Zwaenepoel was on the faculty at Rice University, where he was the Karl F. Hasselmann Professor of Computer Science and Electrical and Computer Engineering.
He was elected Fellow of the IEEE in 1998, and Fellow of the ACM in 2000. In 2000 he received the Rice University Graduate Student Association Teaching and Mentoring Award. In 2007 he received the IEEE Tsutomu Kanai award. He was elected to the European Academy in 2009. He won best paper awards at SigComm 1984, OSDI 1999, Usenix 2000, Usenix 2006 and Eurosys 2007. He was program chair of OSDI in 1996 and Eurosys in 2006, and general chair of Mobisys in 2004. He was also an Associate Editor of the IEEE Transactions on Parallel and Distributed Systems from 1998 to 2002.
Willy Zwaenepoel has worked in a variety of aspects of operating and distributed systems, including microkernels, fault tolerance, parallel scientific computing on clusters of workstations, clusters for web services, mobile computing, database replication and virtualization. He is most well known for his work on the Treadmarks distributed shared memory system, which was licensed to Intel and became the basis for Intels OpenMP cluster product. His work on high-performance software for network I/O led to the creation of iMimic Networking, Inc, which he led from 2000 to 2005. His current interests include large-scale data stores and software testing. Most recently, his work in software testing led to the creation of BugBuster, a startup based in Lausanne.
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).
