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.
Andrea RidolfiI am a professor of Signal Processing and Communication Technologies at Bern University of Applied Sciences.
Since 2004 I hold a lecturer position at EPFL, teaching “Mathematical Principles of Signal Processing” (Doctoral School, 2004 – 2011), “Statistical Signal and Data Processing through Applications” (Master Program, (2004 – ongoing), and Signal Processing and Machine Learning for Digital Humanities (Master, 2017 – 2019, co-taught with Mathieu Salzmann).
Previously, I have been working as Project Manager and R&D Engineer at EPFL (2011-2014), coordinating the LCAV activities within the NSF – Nanotera project Opensense, and as Project Manager and R&D Engineer with the biomedical signal processing group at CSEM (2006-2011).
Michele CeriottiMichele Ceriotti received his Ph.D. in Physics from ETH Zürich in 2010. He spent three years in Oxford as a Junior Research Fellow at Merton College. Since 2013 he leads the laboratory for Computational Science and Modeling in the Institute of Materials at EPFL. His research revolves around the atomic-scale modelling of materials, based on the sampling of quantum and thermal fluctuations and on the use of machine learning to predict and rationalize structure-property relations. He has been awarded the IBM Research Forschungspreis in 2010, the Volker Heine Young Investigator Award in 2013, an ERC Starting Grant in 2016, and the IUPAP C10 Young Scientist Prize in 2018.
Pina MarzilianoPina Marziliano obtained her Bachelors of Science degree in Applied Mathematics and Masters of Science degree in Computer Science in 1994 and 1996, respectively, from the Universite de Montreal. She completed the pioneering Doctoral School program in the Communications Systems Department at the EPFL in 1997 and obtained her PhD degree in 2001. Her professional career began as a Senior Research Engineer in a start-up company called Genimedia SA in Lausanne, Switzerland where she developed perceptual quality metrics for multimedia applications which led her to two highly cited (>100) journal and conference papers, as well as, the filing of a patent. In 2003, she became an Assistant Professor for the Division of Information Engineering in the School of Electrical and Electronic Engineering at the Nanyang Technological University in Singapore focusing her research in biomedical signal and image processing. In 2006, she was seconded to NTU’s International Relations Office for one year where she co-strategized the university international partnerships and conceptualised the Global Partnership Management and Analysis Tool. She received the IEEE Signal Processing Society 2006 Best Paper Award for the article entitled "Sampling Signals with Finite Rate of Innovation" co-authored with Martin Vetterli and Thierry Blu. Later that year patents on the same topic were acquired by Qualcomm Inc., USA, followed by consultancy work which led to obtaining US200KindustryresearchgrantfromQualcomm. In2009,aworkshopco−organisedbyNTU’sCollegeofEngineeringandTanTockSengHospitalandpartneroftheNTU−ImperialCollegeMedicalSchoolsparkedseveralresearchcollaborationswithdoctorsfromtheOphthalmologyDepartmentandDiagnosticRadiologyDepartmentwhichhaveledtojointinternationalconferenceandjournalpublications,significant(>SGD3M) joint research funding and a granted US patent. Apart from her research achievements, she has served as an Associate Editor for IEEE Signal Processing Letters, IEEE Transactions on Signal Processing, a technical reviewer for more than a dozen international conference and Tier-1 journal publications, as well as, a Technical Program Committee member of international conferences and voted in as member of the highly selective Signal Processing Theory and Methods Technical Committee in the IEEE Signal Processing Society. She has served as the Chair of the IEEE Singapore Section Women In Engineering (WIE) Affinity Group where she spearheaded and co-organized monthly technical and social activities, thus increasing the group’s visibility in the IEEE Singapore Section. With her leadership and initiatives, the group received the 2009 Honourable Mention Women in Engineering Affinity Group of the Year Award from the IEEE WIE Committee in the USA. In 2011, she was the General Chair of the 9th International Conference on Sampling Theory and Applications, co-organised by the School of EEE and School of Physical and Mathematical Sciences, NTU. This interdisciplinary conference and flagship event of her research community was held for the first time in Asia on the NTU campus. It gathered 132 participants comprising of mathematicians, engineers and applied scientists from 26 countries around the globe. In 2012, she was tenured and promoted to Associate Professor at the Nanyang Technological University in Singapore. Besides pursuing her academic career, she has been actively involved in technology transfer and entrepreneurship co-founding a design company (PABensen) and a biotechnology spin-off BIORITHM. In 2019, Pina Marziliano was appointed Executive Director of the Centre for Biomedical Imaging (CIBM), a centre composed of five partner institutions HUG, UNIGE, EPFL, UNIL and CHUV located in a 50km radius of the Lemans region in Switzerland. The unique union of reputable clinicians, academics and researchers combined with the capabilities of developing cutting edge technology and housing the latest state-of-the art equipment, is her source of inspiration and drive in leading CIBM, a world reknowned Centre of Excellence in Biomedical Imaging. David Andrew BarryResearch InterestsSubsurface hydrology, constructed wetlands, ecological engineering, in particular contaminant transport and remediation of soil and groundwater; more generally, models of hydrological and vadose zone processes; application of mathematical methods to hydrological processes; coastal zone sediment transport, aquifer-coastal ocean interactions; hydrodynamics and modelling of lakes.
Anthony Christopher DavisonAnthony Davison has published on a wide range of topics in statistical theory and methods, and on environmental, biological and financial applications. His main research interests are statistics of extremes, likelihood asymptotics, bootstrap and other resampling methods, and statistical modelling, with a particular focus on the first currently. Statistics of extremes concerns rare events such as storms, high winds and tides, extreme pollution episodes, sporting records, and the like. The subject has a long history, but under the impact of engineering and environmental problems has been an area of intense development in the past 20 years. Davison''s PhD work was in this area, in a project joint between the Departments of Mathematics and Mechanical Engineering at Imperial College, with the aim of modelling potential high exposures to radioactivity due to releases from nuclear installations. The key tools developed, joint with Richard Smith, were regression models for exceedances over high thresholds, which generalized earlier work by hydrologists, and formed the basis of some important later developments. This has led to an ongoing interest in extremes, and in particular their application to environmental and financial data. A major current interest is the development of suitable methods for modelling rare spatio-temporal events, particularly but not only in the context of climate change. Likelihood asymptotics too have undergone very substantial development since 1980. Key tools here have been saddlepoint and related approximations, which can give remarkably accurate approximate distribution and density functions even for very small sample sizes. These approximations can be used for wide classes of parametric models, but also for certain bootstrap and resampling problems. The literature on these methods can seem arcane, but they are potentially widely applicable, and Davison wrote a book joint with Nancy Reid and Alessandra Brazzale intended to promote their use in applications. Bootstrap methods are now used in many areas of application, where they can provide a researcher with accurate inferences tailor-made to the data available, rather than relying on large-sample or other approximations of doubtful validity. The key idea is to replace analytical calculations of biases, variances, confidence and prediction intervals, and other measures of uncertainty with computer simulation from a suitable statistical model. In a nonparametric situation this model consists of the data themselves, and the simulation simply involves resampling from the existing data, while in a parametric case it involves simulation from a suitable parametric model. There is a wide range of possibilities between these extremes, and the book by Davison and Hinkley explores these for many data examples, with the aim of showing how and when resampling methods succeed and why they can fail. He was Editor of Biometrika (2008-2017), Joint Editor of Journal of the Royal Statistical Society, series B (2000-2003), editor of the IMS Lecture Notes Monograph Series (2007), Associate Editor of Biometrika (1987-1999), and Associate Editor of the Brazilian Journal of Probability and Statistics (1987 2006). Currently he on the editorial board of Annual Reviews of Statistics and its Applications. He has served on committees of Royal Statistical Society and of the Institute of Mathematical Statistics. He is an elected Fellow of the American Statistical Assocation and of the Institute of Mathematical Statistics, an elected member of the International Statistical Institute, and a Chartered Statistician. In 2009 he was awarded a laurea honoris causa in Statistical Science by the University of Padova, in 2011 he held a Francqui Chair at Hasselt University, and in 2012 he was Mitchell Lecturer at the University of Glasgow. In 2015 he received the Guy Medal in Silver of the Royal Statistical Society and in 2018 was a Medallion Lecturer of the Institute of Mathematical Statistics.
