Babak FalsafiBabak is a Professor in the School of Computer and Communication Sciences and the founding director of the EcoCloud, an industrial/academic consortium at EPFL investigating scalable data-centric technologies. He has made numerous contributions to computer system design and evaluation including a scalable multiprocessor architecture which was prototyped by Sun Microsystems (now Oracle), snoop filters and memory streaming technologies that are incorporated into IBM BlueGene/P and Q and ARM cores, and computer system performance evaluation methodologies that have been in use by AMD, HP and Google PerKit . He has shown that hardware memory consistency models are neither necessary (in the 90's) nor sufficient (a decade later) to achieve high performance in multiprocessor systems. These results eventually led to fence speculation in modern microprocessors. His latest work on workload-optimized server processors laid the foundation for the first generation of Cavium ARM server CPUs, ThunderX. He is a recipient of an NSF CAREER award, IBM Faculty Partnership Awards, and an Alfred P. Sloan Research Fellowship. He is a fellow of IEEE and ACM.
Mohammad Amin ShokrollahiAmin Shokrollahi has worked on a variety of topics, including coding theory, computational number theory and algebra, and computational/algebraic complexity theory. He is best known for his work on iterative decoding algorithms of graph based codes, an area in which he holds a number of granted and pending patents. He is the co-inventor of Tornado codes, and the inventor of Raptor codes. His codes have been standardized and successfully deployed in practical areas dealing with data transmission over lossy networks.
Prior to joining EPFL, Amin Shokrollahi has held positions as the chief scientist of Digital Fountain, member of the technical staff at Bell Laboratories, senior researcher at the International Computer Science Insitute in Berkeley, and assistant professor at the department of computer science of the university of Bonn. He is a Fellow of the IEEE, and he was awarded the Best Paper Award of the IEEE IT Society in 2002 for his work on iterative decoding of LDPC code, the IEEE Eric Sumner Award in 2007 for the development of Fountain Codes, and the joint Communication Society/Information Theory Society best paper award of 2007 for his paper on Raptor Codes.
Stephan MorgenthalerACADEMIC POSITIONS
Professor of Applied Statistics, EPFL, 1988-present
Associate Professor of Statistics, Yale University, 1987-1988
Assistant Professor of Statistics, Yale University, 1983-1987
Instructor of Mathematics, Massachusetts Institute of Technology, 1983-1984
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.
Charles StuartD'origine britannique, Charles Alexander Stuart est né à Newmachar (Ecosse) le 5 juin 1945. Il étudie les mathématiques à l'Université d'Aberdeen, où il obtient une licence (B.Sc.) en 1967, et à Oxford, où il a fait son doctorat (D.Phil) en 1970.
De 1970 à 1974, il est lecteur au Département de mathématiques de l'Université du Sussex. Un congé lui permet de passer deux ans (1973-1975) à Genève, comme chercheur à l'Institut Battelle. Pendant l'année académique 1975-1976, il est lecteur à l'Université d'Aberdeen. Il est nommé professeur extraordinaire à l'EPFL en 1975 et professeur ordinaire en 1982.
Il donne des cours d'analyse à plusieurs sections d'ingénieurs (1er cycle). Pour les 2e et 3e cycles, il traite les équations différentielles et l'analyse fonctionnelle. Ses recherches portent sur les mêmes branches; elles concernent surtout des problèmes de bifurcation qui se présentent dans la modélisation de phénomènes physiques.
Il a passé un premier congé sabbatique (1982-1983) à l'Université de Heriot-Watt et un deuxième (1989-1990) à l'Université Cornell, aux Etats-Unis
Bernard DacorognaAprès avoir obtenu sa licence ès sciences mathématiques à l'Université de Genève, puis une maîtrise (Master of Science) à l'Université d'Aberdeen (G.B.), il reçoit son doctorat (Ph.D.) de l'Université Heriot-Watt (G.B.) en 1980. Il rejoint l'EPFL en 1981, après une année à Brown University (E.U.). Il est nommé professeur ordinaire au département de mathématiques de l'EPFL en 2003. Son enseignement porte sur des cours d'analyse. Ses recherches, qui ont abouti à la publication de plusieurs livres et d'une centaine d'articles, sont dans le domaine des équations aux dérivées partielles et du calcul des variations.
