Claudia Rebeca Binder SignerClaudia R. Binder, a Swiss, Canadian and Colombian citizen, was born in Montreal and spent most of her childhood in Switzerland and Colombia. She studied at ETH Zurich from 1985 to 1996, earning a degree in biochemistry and then a PhD in environmental sciences. After conducting her post-doctoral research at the University of Maryland in the US from 1996 to 1998, she returned to Switzerland and took a position as a senior research scientist at ETH Zurich, studying the interaction between human and environmental systems at the Institute for Natural and Social Science Interface. In 2006, Binder joined the University of Zurich as an assistant professor in the Department of Geography, and in 2009 moved to the University of Graz in Austria where she served as a full professor of systems science. In 2011, she took a position at the University of Munich’s Department of Geography as a full professor of human-environment relations.
Binder joined EPFL in March 2016 and set up the Laboratory for Human-Environment Relations in Urban Systems (HERUS) at ENAC; she also holds the La Mobilière Chair on Urban Ecology and Sustainable Living.
Her research involves analyzing, modelling and assessing the transition of urban systems towards sustainability. She looks in particular at how we can better understand the dynamics of urban metabolism, what characterizes a sustainable city, and what drives and hinders transformation processes. She does so by combining knowledge from social, natural and data science. Her research focuses on food, energy, and sustainable living and transport in urban systems.
In Switzerland, Binder was appointed to the Research Council, Programs Division of the Swiss National Science Foundation (SNSF) in 2016 and serves on the Steering Committee of the SNSF’s National Research Program 71, “Managing Energy Consumption” and the Swiss Competence Centers for Energy Research (SCCER). She is also a member of the Steering Board on Sustainability Research for the Swiss Academies of Arts and Sciences. In 2019, she was elected as a member of the University Council of the University of Munich (LMU).
At EPFL, Binder is the academic director of Design Together, a cross-disciplinary teaching initiative. She was appointed to the management team of the Energy Center in 2018 and as head of the working group on EPFL’s energy and sustainability strategy in 2019.
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.
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
Francesco MondadaDr. Mondada received his M.Sc. in micro-engineering in 1991 and his Doctoral degree in 1997 at EPFL. During his thesis he co-founded the company K-Team, being both CEO and president of the company for about 5 years. He is one of the three main developers of the Khepera robot, considered as a standard in bio-inspired robotics and used by more than 1,000 universities and research centers worldwide. Fully back in research in 2000 and after a short period at CALTECH, he participated to the SWARM-BOTS project as the main developer of the s-bot robot platform, which was ranked on position 39 in the list of The 50 Best Robots Ever (fiction or real) by the Wired Journal in 2006. The SWARM-BOTS project was selected as FET-IST success story by the EU commission. He is author of more than 100 papers in the field of bio-inspired robotics and system level robot design. He is co-editor of several international conference proceedings. In November 2005 he received the EPFL Latsis University prize for his contributions to bio-inspired robotics. In 2011 he received the "Crédit Suisse Award for Best Teaching" from EPFL and in 2012 the "polysphère" award from the students as best teacher in the school of engineering. His interests include the development of innovative mechatronic solutions for mobile and modular robots, the creation of know-how for future embedded applications, and making robot platforms more accessible for education, research, and industrial development.
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.
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.
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