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.
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).
Jürg Alexander SchiffmannAfter obtaining his diploma in mechanical engineering from EPFL in 1999 he co-founded a start-up company dedicated to the design of gas bearing supported rotors. In 2005 he joined Fischer Engineering Solutions where he led the development of small-scale, gas bearing supported high-speed turbomachinery for fuel cell air supplies and for domestic scale heat pumps. In parallel he worked on his PhD, which he obtained from EPFL in 2008 and for which he was awarded the SwissElectric Research Award. He then joined the Gas Turbine Lab at MIT as a postdoctoral associate where he worked on foil bearings and on the experimental investigation of radial diffusers. In 2013 he was nominated assistant professor at the Ecole Polytechnique Fédérale de Lausanne where he founds the Laboratory for Applied Mechanical Design. His current research interest are in gas lubricated bearings, in aerodynamics of small-scale compressors and turbines and in automated design and optimization methodologies.
Sneha JainSneha Jain is currently conducting her PhD thesis on the influence of ocular characteristics and colour of light on discomfort glare from daylight at workplaces. She completed her undergraduate degree in architecture and has a Master of Science in Building Science from International Institute of Information Technology in Hyderabad, India. Her Master thesis was on Daylight glare estimation for open-loop window roller shade control system to optimize daylight levels and visual comfort in a lab setup. She also worked as a research fellow at Lawrence Berkeley National Lab in Berkeley, California. Her current work focuses on improving the prediction of current discomfort glare models.
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).
Philippe RenaudPhilippe Renaud is Professor at the Microsystem Laboratory (LMIS4) at EPFL. He is also the scientific director of the EPFL Center of MicroNanoTechnology (CMI). His main research area is related to micronano technologies in biomedical applications (BioMEMS) with emphasis on cell-chips, nanofluidics and bioelectronics. Ph. Renaud is invloved in many scientifics papers in his research area. He received his diploma in physics from the University of Neuchâtel (1983) and his Ph.D. degree from the University of Lausanne (1988). He was postdoctoral fellow at University of California, Berkeley (1988-89) and then at the IBM Zürich Research Laboratory in Switzerland (1990-91). In 1992, he joined the Sensors and Actuators group of the Swiss Center for Electronics and Microtechnology (CSEM) at Neuchâtel, Switzerland. He was appointed assistant professor at EPFL in 1994 and full professor in 1997. In summer 1996, he was visiting professor at the Tohoku University, Japan. Ph. Renaud is active in several scientific committee (scientific journals, international conferences, scientific advisory boards of companies, PhD thesis committee). He is also co-founder of the Nanotech-Montreux conference. Ph. Renaud is committed to valorization of basic research through his involvement in several high-tech start-up companies.
