Paolo IennePaolo Ienne has been a Professor at the EPFL since 2000 and heads the Processor Architecture Laboratory (LAP). Prior to that, he worked for the Semiconductors Group of Siemens AG, Munich, Germany (which later became Infineon Technologies AG) where he was at the head of the Embedded Memories unit in the Design Libraries division. His research interests include various aspects of computer and processor architecture, FPGAs and reconfigurable computing, electronic design automation, and computer arithmetic. Ienne was a recipient of Best Paper Awards at the 20th, 24th, and 28th ACM/SIGDA International Symposia on Field-Programmable Gate Arrays (FPGA), in 2012, 2016 and 2020, at the 19th and 30th International Conference on Field-Programmable Logic and Applications (FPL), in 2009 and 2020, at the International Conference on Compilers, Architectures, and Synthesis for Embedded Systems (CASES), in 2007, and at the 40th Design Automation Conference (DAC), in 2003; many other papers have been candidates to Best Paper Awards in prestigious venues. He has served as general, programme, and topic chair of renown international conferences, including organizing in Lausanne the 26th International Conference on Field-Programmable Logic and Applications (FPL) in 2016. He serves on the steering committee of the IEEE Symposium on Computer Arithmetic (ARITH) and of the International Conference on Field-Programmable Logic and Applications (FPL). Ienne has guest edited a number of special issues and special sections on various topics for IEEE and ACM journals. He is regularly member of program committees of international workshops and conferences in the areas of design automation, computer architecture, embedded systems, compilers, FPGAs, and asynchronous design. He has been an associate editor of ACM Transactions on Architecture and Code Optimization (TACO), since 2015, of ACM Computing Surveys (CSUR), since 2014, and of ACM Transactions on Design Automation of Electronic Systems (TODAES) from 2011 to 2016.
Pascal FrossardTeaching & PhD PhD Students Yiming Qin, Alba Carballo Castro, Elisa Messori, Ke Wang, Sevda Ögüt, Tuna Alikasifoglu, William Cappelletti, Manuel Madeira, Mahdi Amiri, Ortal Yona Senouf, Vasiliki Rizou, Cem Bilaloglu, Abdellah Rahmani, Amel Abdelraheem, Jérémy Jean Philippe Baffou, Adam Hazimeh, Vincent Jung, Yike Zhao Past EPFL PhD Students Dan Jurca, Jean-Paul Wagner, Ivana Radulovic, Ivana Tosic, Effrosyni Kokiopoulou, Zafer Arican, Vijayaraghavan Thirumalai, Tamara Tosic, Eirina Bourtsoulatze, Elif Vur
Friedrich EisenbrandEnseignement et PhD Doctorant·es actuel·les Ruben Manuel Skorupinski, Neta Singer, Lukas Vogl, Jiaye Wei A dirigé les thèses EPFL de Thomas Rothvoss, Nicolai Hähnle, Martin Niemeier, Adrian Aloysius Bock, Carsten Moldenhauer, Alfonso Bolívar Cevallos Manzano, Manuel Francesco Aprile, Igor Malinovic, Christoph Hunkenschröder, Moritz Andreas Venzin, Jana Tabea Cslovjecsek A co-dirigé les thèses EPFL de Puck van Gerwen Cours Algèbre linéaire avancée II - diagonalisation MATH-115(a) L'objectif
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.
Lenka ZdeborováLenka Zdeborová is a Professor of Physics and of Computer Science in École Polytechnique Fédérale de Lausanne where she leads the Statistical Physics of Computation Laboratory. She received a PhD in physics from University Paris-Sud and from Charles University in Prague in 2008. She spent two years in the Los Alamos National Laboratory as the Director's Postdoctoral Fellow. Between 2010 and 2020 she was a researcher at CNRS working in the Institute of Theoretical Physics in CEA Saclay, France. In 2014, she was awarded the CNRS bronze medal, in 2016 Philippe Meyer prize in theoretical physics and an ERC Starting Grant, in 2018 the Irène Joliot-Curie prize, in 2021 the Gibbs lectureship of AMS. She is an editorial board member for Journal of Physics A, Physical Review E, Physical Review X, SIMODS, Machine Learning: Science and Technology, and Information and Inference. Lenka's expertise is in applications of concepts from statistical physics, such as advanced mean field methods, replica method and related message-passing algorithms, to problems in machine learning, signal processing, inference and optimization. She enjoys erasing the boundaries between theoretical physics, mathematics and computer science.
Oliver JanzerEnseignement et PhD Doctorant·es actuel·les Rik Sarkar Cours Algebraic methods in combinatorics MATH-526 Dans ce cours, nous étudions comment les méthodes algébriques peuvent être utilisées pour résoudre des problèmes de combinatoire. Les principaux outils utilisés proviennent de l'algèbre linéaire et de la théorie des polynômes. Graph theory MATH-360 Le cours introduit les concepts de base et certains résultats de la théorie moderne des graphes.
Sébastien MarcelEnseignement et PhD Doctorant·es actuel·les Parsa Rahimi Noshanagh A co-dirigé les thèses EPFL de Fabien Cardinaux, Yann Rodriguez, Agnès Just, Guillaume Heusch, Anindya Roy, Venkatesh Bala Subburaman, Cosmin Atanasoaei, Laurent El Shafey, Ivana Chingovska, Tiago De Freitas Pereira, Amir Mohammadi, Alexander Unnervik, Hatef Otroshi Shahreza
Sofia Charlotta OlhedeSofia Olhede is a professor of Statistics at EPFL in Switzerland. She joined UCL prior to this in 2007, before which she was a senior lecturer of statistics (associate professor) at Imperial College London (2006-2007), a lecturer of statistics (assistant professor) (2002-2006), where she also completed her PhD in 2003 and MSci in 2000. She has held three research fellowships while at UCL: UK Engineering and Physical Sciences Springboard fellowship as well as a five-year Leadership fellowship, and now holds a European Research Council Consolidator fellowship. Sofia has contributed to the study of stochastic processes; time series, random fields and networks. Sofia was part of the multi-institutional team that set up the UK national data science institute, the Alan Turing Institute. She organised and served as chair of the science committee that developed the initial 500 000 pounds scientific programme of the institute; peer-reviewing over 100 workshop proposals and hosting over 30. She also chaired the first recruitment wave of the institute hiring 13 data scientists as a multi-university recruitment drive. Sofia was a member of the Royal Society and British Academy Data Governance Working Group, and the Royal Society working group on machine learning. Most recently she was one of 3 commissioners on a law society commission on the usage of algorithms in the justice system.
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