Concept
Lack-of-fit sum of squares
Related people (14)
Colin Neil Jones
Colin Jones is an Associate Professor in the Automatic Control Laboratory at the Ecole Polytechnique Federale de Lausanne (EPFL) in Switzerland. He was a Senior Researcher at the Automatic Control Lab at ETH Zurich until 2011 and obtained a PhD in 2005 from the University of Cambridge for his work on polyhedral computational methods for constrained control. Prior to that, he was at the University of British Columbia in Canada, where he took a BASc and MASc in Electrical Engineering and Mathematics. Colin has worked in a variety of industrial roles, ranging from commercial building control to the development of custom optimization tools focusing on retail human resource scheduling. His current research interests are in the theory and computation of predictive control and optimization, and their application to green energy generation, distribution and management.
Michael Christoph Gastpar
Michael Gastpar is a (full) Professor at EPFL. From 2003 to 2011, he was a professor at the University of California at Berkeley, earning his tenure in 2008.
He received his Dipl. El.-Ing. degree from ETH Zürich, Switzerland, in 1997 and his MS degree from the University of Illinois at Urbana-Champaign, IL, USA, in 1999. He defended his doctoral thesis at EPFL on Santa Claus day, 2002. He was also a (full) Professor at Delft University of Technology, The Netherlands.
His research interests are in network information theory and related coding and signal processing techniques, with applications to sensor networks and neuroscience.
He is a Fellow of the IEEE. He is the co-recipient of the 2013 Communications Society & Information Theory Society Joint Paper Award. He was an Information Theory Society Distinguished Lecturer (2009-2011). He won an ERC Starting Grant in 2010, an Okawa Foundation Research Grant in 2008, an NSF CAREER award in 2004, and the 2002 EPFL Best Thesis Award. He has served as an Associate Editor for Shannon Theory for the IEEE Transactions on Information Theory (2008-11), and as Technical Program Committee Co-Chair for the 2010 International Symposium on Information Theory, Austin, TX.
Martin Vetterli
Martin Vetterli was appointed president of EPFL by the Federal Council following a selection process conducted by the ETH Board, which unanimously nominated him.
Professor Vetterli was born on 4 October 1957 in Solothurn and received his elementary and secondary education in Neuchâtel Canton. He earned a Bachelor’s degree in electrical engineering from ETH Zurich (ETHZ) in 1981, a Master’s of Science degree from Stanford University in 1982, and a PhD from EPFL in 1986. Professor Vetterli taught at Columbia University as an assistant and then associate professor. He was subsequently named full professor in the Department of Electrical Engineering and Computer Sciences at the University of California at Berkeley before returning to EPFL as a full professor at the age of 38. He has also taught at ETHZ and Stanford University.
Professor Vetterli has earned numerous national and international awards for his research in electrical engineering, computer science and applied mathematics, including the National Latsis Prize in 1996. He is a fellow of both the Association for Computing Machinery and the Institute of Electrical and Electronics Engineers and a member the US National Academy of Engineering. He has published over 170 articles and three reference works.
Professor Vetterli’s work on the theory of wavelets, which are used in signal processing, is considered to be of major importance by his peers, and his areas of expertise, including image and video compression and self-organized communication systems, are central to the development of new information technologies. As the founding director of the National Centre of Competence in Research on Mobile Information and Communication Systems, Professor Vetterli is a staunch advocate of transdisciplinary research.
Professor Vetterli knows EPFL inside and out. An EPFL graduate himself, he began been teaching at the school in 1995, was vice president for International Affairs and then Institutional Affairs from 2004 to 2011, and served as dean of the School of Computer and Communication Sciences in 2011 and 2012. In addition to his role as president of the National Research Council of the Swiss National Science Foundation, a position he held from 2013 to 2016, he heads the EPFL’s Audiovisual Communications Laboratory (LCAV) since 1995.
Professor Vetterli has supported more than 60 students in Switzerland and the United States in their doctoral work and makes a point of following their highly successful careers, whether it is in the academic or business world.
He is the author of some 50 patents, some of which were the basis for start-ups coming out of his lab, such as Dartfish and Illusonic, while others were sold (e.g. Qualcomm) as successful examples of technology transfer. He actively encourages young researchers to market the results of their work.
Roland Longchamp
Roland Longchamp is Professor of Automatic Control and Director of the Automatic Control Laboratory at the Swiss Federal Institute of Technology in Lausanne (EPFL). He received his Diploma in Electrical Engineering and his Ph.D. degree both from EPFL. He was appointed as Postdoctoral Fellow, first at the Information Systems Laboratory, Stanford University, and then at the Decision and Control Laboratory, University of Illinois at Urbana-Champaign, working in the areas of nonlinear systems, estimation theory and predictive control. He was with the Asea Brown Boveri Company in Turgi, Switzerland, involved in the field of on-line control of large power systems. He joined EPFL in 1983, where his current research interests include control of linear systems, adaptive control, robust control, with applications to mechatronic systems. He served as Head of the Mechanical Engineering Department in 1991-1993 and as Director of the Automatic Control Laboratory for the periods 1986-1993 and 1997-2003. He is Editor of the EPFL Press Mechanical Engineering Series since 1996.
Alireza Karimi
Alireza Karimi received his B. Sc. and M. Sc. degrees in Electrical Engineering in 1987 and 1990, respectively, from Amir Kabir University (Tehran Polytechnic). Then he received his DEA and Ph. D. degrees both on Automatic Control from Institut National Polytechnique de Grenoble (INPG) in 1994 and 1997, respectively. He was Assistant Professor at Electrical Engineering Department of Sharif University of Technology in Teheran from 1998 to 2000. Then he joined Automatic Laboratory of Swiss Federal Institute of Technology at Lausanne, Switzerland. He is currently Professor of Automatic Control and the head of "Data-Driven Modelling and Control" group. His research interests include data-driven controller tuning and robust control with application to mechatronic systems and electrical grids.
Jean-Philippe Thiran
Jean-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.