Roberto CastelloRoberto Castello is a senior scientist and group leader at the EPFL Laboratory of Solar Energy and Building Physics. Physicist by training, he has extensive experience in collecting, classifying and interpreting large datasets using advanced data mining techniques and statistical methods. He received his MSc (2007) in Particle Physics and PhD (2010) in Physics and Astrophysics from the University of Torino. He worked as a postdoctoral researcher at the Belgian National Research Fund (2011-2014) and at the CERN Experimental Physics Department (2015-2017) as a research fellow and data scientist. He is primary author of more than 20 peer-reviewed publications and he presented at major international conferences in the high energy physics domain.
In 2018 he joined the Solar Energy and Building Physics Laboratory (LESO-PB) to work on data mining and Machine Learning techniques for the built environment and renewable energy. His main research interests are: spatio-temporal modeling of renewable energy potential, energy consumption forecasting techniques, anomaly detection, and computer vision techniques for automated classification in the built environment.
He leads the group of Urban Data Mining, Intelligence and Simulation at LESO-PB and he is a member of the NRP75 Big Data project (HyEnergy) of the Swiss National Science Foundation. He is a member of the Swiss Competence Centre for Energy Research (SCCER) and deputy leader of the working group on Leveraging Ubiquitous Energy Data. He has served as a scientific committee member, workshop organizer and speaker at international conferences (ICAE 2020, Applied Machine Learning Days 2019 and 2020, CISBAT 2019 and 2021 and SDS2020).
Since 2017 he is member of the Geneva 2030 Ecosystem network, promoting the United Nations agenda towards the realization of the Sustainable Development Goals (SDGs).
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
Pierre VandergheynstPierre Vandergheynst received the M.S. degree in physics and the Ph.D. degree in mathematical physics from the Université catholique de Louvain, Louvain-la-Neuve, Belgium, in 1995 and 1998, respectively. From 1998 to 2001, he was a Postdoctoral Researcher with the Signal Processing Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. He was Assistant Professor at EPFL (2002-2007), where he is now a Full Professor of Electrical Engineering and, by courtesy, of Computer and Communication Sciences. As of 2015, Prof. Vandergheynst serves as EPFL’s Vice-Provost for Education. His research focuses on harmonic analysis, sparse approximations and mathematical data processing in general with applications covering signal, image and high dimensional data processing, computer vision, machine learning, data science and graph-based data processing. He was co-Editor-in-Chief of Signal Processing (2002-2006), Associate Editor of the IEEE Transactions on Signal Processing (2007-2011), the flagship journal of the signal processing community and currently serves as Associate Editor of Computer Vision and Image Understanding and SIAM Imaging Sciences. He has been on the Technical Committee of various conferences, serves on the steering committee of the SPARS workshop and was co-General Chairman of the EUSIPCO 2008 conference. Pierre Vandergheynst is the author or co-author of more than 70 journal papers, one monograph and several book chapters. He has received two IEEE best paper awards. Professor Vandergheynst is a laureate of the Apple 2007 ARTS award and of the 2009-2010 De Boelpaepe prize of the Royal Academy of Sciences of Belgium.
Joaquim Loizu CisquellaJoaquim Loizu graduated in Physics at the École Polytechnique Fédérale de Lausanne, carrying out his Master thesis project at the Center for Bio-Inspired Technology, Imperial College London, on the theoretical and numerical study of the biophysics of light-sensitive neurons. In 2009, he started his PhD studies with Prof. Paolo Ricci at the Swiss Plasma Center, the major plasma and fusion laboratory in Switzerland. His thesis focused on the theory of plasma-wall interactions and their effect on the mean flows and turbulence in magnetized plasmas. He obtained his PhD in December 2013. In 2014, he joined the Max-Planck-Princeton Center for plasma research as a Postdoctoral Research Fellow, spending one year at the Princeton Plasma Physics Laboratory and one year at the Max-Planck-Institute for Plasma Physics in Greifswald, Germany. During this time, he worked on three-dimensional magnetohydrodynamics, studying the formation of singular currents and magnetic islands at rational surfaces. In 2016, he obtained a two-years Eurofusion Postdoctoral Fellowship to carry out research at the Max-Planck-Institute for Plasma Physics in Greifswald, Germany. During this time, he focused on the computation of 3D MHD equilibria in stellarators, including the possibility of magnetic islands and magnetic field-line chaos. In 2018, he joined the Swiss Plasma Center as a Scientist and Lecturer. He is also one of the leaders of the Simons Collaboration on Hidden Symmetries and Fusion Energy. His current research interests include MHD equilibrium and stability, magnetic reconnection, self-organization, non-neutral plasmas, plasma sheaths, and plasma transport in chaotic magnetic fields.
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.
Christian Gabriel TheilerChristian Theiler obtained his Master’s degree in physics from ETH Zurich in 2007 and his PhD from EPFL in 2011. He then joined MIT as a postdoctoral associate to work on the Alcator C-Mod tokamak. In 2014, he returned to EPFL as a EUROfusion fellow, to join the TCV tokamak team. Two years later, he was named Tenure Track Assistant Professor in Plasma Physics at EPFL. Christian’s research focuses on tokamak boundary physics and related diagnostic techniques. He has contributed to the understanding of the formation, propagation, and control of turbulent plasma structures, called blobs, and gained new insights on the structure of transport barriers in the plasma periphery in different high-confinement regimes. His current research focuses on detachment physics and turbulence characteristics in conventional and alternative divertor magnetic geometries.
