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).
Jean-Philippe ThiranJean-Philippe Thiran was born in Namur, Belgium, in August 1970. He received the Electrical Engineering degree and the PhD degree from the Université catholique de Louvain (UCL), Louvain-la-Neuve, Belgium, in 1993 and 1997, respectively. From 1993 to 1997, he was the co-ordinator of the medical image analysis group of the Communications and Remote Sensing Laboratory at UCL, mainly working on medical image analysis. Dr Jean-Philippe Thiran joined the Signal Processing Institute (ITS) of the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in February 1998 as a senior lecturer. He was promoted to Assistant Professor in 2004, to Associate Professor in 2011 and is now a Full Professor since 2020. He also holds a 20% position at the Department of Radiology of the University of Lausanne (UNIL) and of the Lausanne University Hospital (CHUV) as Associate Professor ad personam. Dr Thiran's current scientific interests include
Computational medical imaging: acquisition, reconstruction and analysis of imaging data, with emphasis on regularized linear inverse problems (compressed sensing, convex optimization). Applications to medical imaging: diffusion MRI, ultrasound imaging, inverse planning in radiotherapy, etc.Computer vision & machine learning: image and video analysis, with application to facial expression recognition, eye tracking, lip reading, industrial inspection, medical image analysis, etc.
Nicolas MacrisNicolas Macris received the PhD degree in theoretical physics from EPFL and then pursued his scientific activity at the mathematics department of Rutgers University (NJ, USA). He then joined the Faculty of Basic Science of EPFL, working in the field of quantum statistical mechanics and mathematical aspects of the quantum Hall effect. Since 2005 he is with the Communication Theories Laboratory and Information Processing group of the School of Communication and Computer Science and currently works at the interface of statistical mechanics, information theory and error correcting codes, inference and learning theory. He held long-term visiting appointments and collaborations with the University College and the Institute of Advanced studies in Dublin, the Ecole Normale Supérieure de Lyon, the Centre de Physique Theorique Luminy Marseille, Paris XI Orsay, the ETH Zürich and more recently Los Alamos National Lab. CV and publication list.
Ralf SeifertRalf W. Seifert is Professor of Technology & Operations Management (TOM) at the College of Management of Technology (CDM) at Ecole Polytechnique Fédérale de Lausanne (EPFL) since 2003. His primary research and teaching interests relate to operations management, supply chain strategy and technology network management. He is also active in industry analysis, international project work and new venture formation.
Based on his work with companies, Professor Seifert has co-authored more than 30 case studies covering different industries. These efforts have been recognized by multiple international case awards granted by EFMD in 2018, 2012, 2009 and 2003, ECCH in 2011 and 2006, as well as POMS in 2004. He continues to actively research issues of supply chain strategy, supply chain finance and technology management and has more than 70 articles and international conference presentations to his credit. In addition, he co-authored two books: one focused on strategic supply chain management and another one concerning start-up challenges of technology ventures.
In parallel to his appointment at EPFL, he continues to serve a position at IMD, were he has been appointed Professor of Operations Management in 2000. Prior to joining IMD, Professor Seifert studied and worked in Germany, Japan and the US. He earned PhD and MS degrees in Management Science at Stanford University, a Diplom Ingenieur degree in Mechanical Engineering at the Karlsruhe Institute of Technology (KIT) and a Master's degree in Integrated Manufacturing Systems Engineering from North Carolina State University. While in the US, he consulted for Hewlett-Packard and served as Teaching and Research Assistant at Stanford University. In Germany he worked for Booz & Company, McKinsey & Company and Freudenberg & Co. In addition, he spent one year as a Visiting Scholar in Operations Research at Waseda University in Tokyo.
