Concept

Point process

Related people (16)
Andrea Ridolfi
I 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).
Patrick Thiran
Patrick Thiran is a full professor in network and systems theory at the School of Computer and Communication Sciences at EPFL. He holds an electrical engineering degree from the Université Catholique de Louvain, Louvain-la-Neuve, Belgium, an M.Sc. degree in electrical engineering from the University of California at Berkeley, USA, and he received the PhD degree from EPFL, in 1996. He became an adjunct professor in 1998, an assistant professor in 2002, an associate professor in 2006 and a full professor in 2011. He was with Sprint Advanced Technology Labs in Burlingame, California, in 2000-01. His research interests are in communication and social networks, performance analysis and stochastic models. He is currently active in the analysis and design of wireless and PLC networks (scaling laws, medium access control), in network monitoring (network tomography, multi-layer networks), and data-driven network science. He also contributed to network calculus and to the theory of locally coupled neural networks and self-organizing maps. He served as an associate editor for the IEEE Transactions on Circuits and Systems in 1997-99 and for the IEEE/ACM Transactions on Networking in 2006-10. He is currently on the editorial board of the IEEE Journal on Selected Areas in Communication. He is/was on the program committee of different conferences in networking, including ACM Sigcomm, Sigmetrics, IMC, CoNext and IEEE Infocom. He was TPC chair of AMC IMC 2011 and CoNext 2012. He is a Fellow of the Belgian American Educational Foundation and of the IEEE. He received the 1996 EPFL Doctoral Prize and the 2008 Crédit Suisse Teaching Award.
Nicolas Macris
Nicolas 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.
Jean-Yves Le Boudec
Jean-Yves Le Boudec is full professor at EPFL and fellow of the IEEE. He graduated from Ecole Normale Superieure de Saint-Cloud, Paris, where he obtained the Agregation in Mathematics in 1980 (rank 4) and received his doctorate in 1984 from the University of Rennes, France. From 1984 to 1987 he was with INSA/IRISA, Rennes. In 1987 he joined Bell Northern Research, Ottawa, Canada, as a member of scientific staff in the Network and Product Traffic Design Department. In 1988, he joined the IBM Zurich Research Laboratory where he was manager of the Customer Premises Network Department. In 1994 he joined EPFL as associate professor.  His interests are in the performance and architecture of communication systems. In 1984, he developed analytical models of multiprocessor, multiple bus computers. In 1990 he invented the concept called "MAC emulation" which later became the ATM forum LAN emulation project, and developed the first ATM control point based on OSPF. He also launched public domain software for the interworking of ATM and TCP/IP under Linux. He proposed in 1998 the first solution to the failure propagation that arises from common infrastructures in the Internet. He contributed to network calculus, a recent set of developments that forms a foundation to many traffic control concepts in the internet.   He earned the Infocom 2005 Best Paper award, with Milan Vojnovic, for elucidating the perfect simulation and stationarity of mobility models, the 2008 IEEE Communications Society William R. Bennett Prize in the Field of Communications Networking, with Bozidar Radunovic, for the analysis of max-min fairness and the 2009 ACM Sigmetrics Best Paper Award, with Augustin Chaintreau and Nikodin Ristanovic, for the mean field analysis of the age of information in gossiping protocols.  He is or has been on the program committee or editorial board of many conferences and journals, including Sigcomm, Sigmetrics, Infocom, Performance Evaluation and ACM/IEEE Transactions on Networking. He co-authored the book "Network Calculus" (2001) with Patrick Thiran and is the author of the book "Performance Evaluation of Computer and Communication Systems" (2010).
Wulfram Gerstner
Wulfram Gerstner is Director of the Laboratory of Computational Neuroscience LCN at the EPFL. His research in computational neuroscience concentrates on models of spiking neurons and spike-timing dependent plasticity, on the problem of neuronal coding in single neurons and populations, as well as on the link between biologically plausible learning rules and behavioral manifestations of learning. He teaches courses for Physicists, Computer Scientists, Mathematicians, and Life Scientists at the EPFL.  After studies of Physics in Tübingen and at the Ludwig-Maximilians-University Munich (Master 1989), Wulfram Gerstner spent a year as a visiting researcher in Berkeley. He received his PhD in theoretical physics from the Technical University Munich in 1993 with a thesis on associative memory and dynamics in networks of spiking neurons. After short postdoctoral stays at Brandeis University and the Technical University of Munich, he joined the EPFL in 1996 as assistant professor. Promoted to Associate Professor with tenure in February 2001, he is since August 2006 a full professor with double appointment in the School of Computer and Communication Sciences and the School of Life Sciences. Wulfram Gerstner has been invited speaker at numerous international conferences and workshops. He has served on the editorial board of the Journal of Neuroscience, Network: Computation in Neural Systems', Journal of Computational Neuroscience', and `Science'.
Ali H. Sayed
Ali H. Sayed is Dean of Engineering at EPFL, Switzerland, where he also leads the Adaptive Systems Laboratory.  He has also served as Distinguished Professor and Chairman of Electrical Engineering at UCLA. He is recognized as a Highly Cited Researcher and is a member of the US National Academy of Engineering. He is also a member of the World Academy of Sciences and served as President of the IEEE Signal Processing Society during 2018 and 2019. Dr. Sayed is an author/co-author of over 570 scholarly publications and six books. His research involves several areas including adaptation and learning theories, data and network sciences, statistical inference, and multiagent systems. His work has been recognized with several major awards including the 2022 IEEE Fourier Award, the 2020 Norbert Wiener Society Award and the 2015 Education Award from the IEEE Signal Processing Society, the 2014 Papoulis Award from the European Association for Signal Processing, the 2013 Meritorious Service Award and the 2012 Technical Achievement Award from the IEEE Signal Processing Society, the 2005 Terman Award from the American Society for Engineering Education, the 2005 Distinguished Lecturer from the IEEE Signal Processing Society, the 2003 Kuwait Prize, and the 1996 IEEE Donald G. Fink Prize. His publications have been awarded several Best Paper Awards from the IEEE (2002, 2005, 2012, 2014) and EURASIP (2015). He is a Fellow of IEEE, EURASIP, and the American Association for the Advancement of Science (AAAS); the publisher of the journal Science.
Pierre Bremaud
De nationalité française, né a Gao (Soudan Français/Mali), Pierre Brémaud est ancien élève de l’Ecole Polytechnique de Paris, et détenteur d’un doctorat de l’Université de Californie à Berkeley, Etats-Unis, en «Electrical Engineering and Computer Science» il est également Docteur ès Sciences Mathématiques de l’Université de Paris 6. Il a successivement dirigé plusieurs groupes de recherche dans le secteur des signaux et systèmes, de la théorie des communications et de la modélisation stochastique. Directeur du Centre de Recherches de l’Ecole Nationale Supérieure de Techniques Avancées (ENSTA) de 1979 à 1985 à Paris, il a été, en parallèle, maître de conférences au département de mathématiques appliquées de l’Ecole Polytechnique (1985-1997) et chef du département de mathématiques de l’ENSTA (1981-1995). M. Brémaud est éditeur associé de plusieurs revues internationales M. Brémaud enseigne à l’EPFL un des trois cours fondamentaux de l’école doctorale en Systèmes de communications. Il compte utiliser sa double formation en mathématiques et en génie électrique pour développer en interaction avec ses collègues un enseignement avancé en modélisation stochastique pour les systèmes de communications. Ses intérêts en recherche concernent la théorie des processus stochastiques (processus ponctuels et files d’attente) et ses applications au filtrage, au contrôle stochastique, à l’évaluation des performances des réseaux de communications, et aux systèmes à événements discrets. Il développe actuellement la théorie des processus de Hawkes linéaires et non linéaires (réseaux stochastiques de «neurones» du type Hopfield), et étudie les modèles du type «saut noise» à la fois comme modèles de trafic dans les réseaux, et comme modèles dans l’analyse des risques dans les assurances.

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