Patrick ThiranPatrick 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.
Maria BrbicMaria Brbic is an assistant professor in computer science at EPFL. Prior to joining EPFL, Maria was a postdoctoral researcher in Computer Science at Stanford University working with Jure Leskovec. She received her PhD degree from University of Zagreb in 2019, while also researching at Stanford University and University of Tokyo. Her research was awarded with the Fulbright Scholarship, L’Oreal UNESCO for Women in Science Scholarship, Branimir Jernej award for outstanding publication in biology and biomedicine, and Josip Loncar Silver Plaque award for the best doctoral dissertation. She has been named a Rising Star in EECS by MIT in 2021. Her research is focused on developing new machine learning methods and applying her methods to advance biomedical research.
Linda MarchandTeaching & PhD Courses Applied statistics MATH-516 The course will provide an overview of everyday challenges in applied statistics through case studies. Students will learn how to use core statistical methods and their extensions, and will use computational and problem-solving tools to provide reproducible solutions for the problems presented. Bioinformatic Analysis of RNA-sequencing (Fall) BIO-693(a) Bioinformatic Analysis of RNA-sequencing (Spring) BIO-693(b)
Laurent Gilles Marie VuillonTeaching & PhD Courses Data visualization COM-480 Understanding why and how to present complex data interactively in an effective manner has become a crucial skill for any data scientist. In this course, you will learn how to design, judge, build and present your own interactive data visualizations.
Christian IseliTeaching & PhD Courses Bioinformatic Analysis of RNA-sequencing (Fall) BIO-693(a) Bioinformatic Analysis of RNA-sequencing (Spring) BIO-693(b) This course will take place at EPFL in June 2026, from 8th to 12th, in room AAC 137.It introduces the workflows and techniques that are used for the analysis of bulk and single-cell RNA-seq data. It empowers students to understand and analyze their own data. Methods: omics in biomedical research BIOENG-519 High-throughp
Nicolas Jean Philippe GuexTeaching & PhD Courses Bioinformatic Analysis of RNA-sequencing (Fall) BIO-693(a) Bioinformatic Analysis of RNA-sequencing (Spring) BIO-693(b) This course will take place at EPFL in June 2026, from 8th to 12th, in room AAC 137.It introduces the workflows and techniques that are used for the analysis of bulk and single-cell RNA-seq data. It empowers students to understand and analyze their own data. Methods: omics in biomedical research BIOENG-519 High-throughp
Samy BengioExpertise
Large Language ModelsReasoningStatistical machine learningSpeech processingPerson authenticationMultimodal processingSequence processingArtificial neural networks, support vector machinesHidden markov models, gaussian mixture modelsetc
Expertise
Large Language ModelsReasoningStatistical machine learningSpeech processingPerson authenticationMultimodal processingSequence processingArtificial neural networks, support vector machinesHidden markov models, gaussian mixture modelsetc
Mission
Samy Bengio
Jean-Philippe PelletTeaching & PhD Courses Data science for engineers with Python ENG-209 This course offers a gradual and comprehensive introduction to the field of Data Science through the Python programming language. It guides students from raw data manipulation to modeling and the extraction of meaningful insights from real-world data.
Jean-Louis ScartezziniDirector of EPFL Solar Energy and Building Physics Laboratory (1994-present); Founder & Director of ENAC Institute of Infrastructures, Resources and Environment (2002-2009); Founder & Director of EPFL Doctoral Program in Environment (2002-2009); Co-Director of EPFL Institute of Building Technology (1994-1997); Associate Professor of Building Physics at EPFL (1994-1997); Associate Professor of Building Physics at University of Geneva (1990-1997); Group Leader & Research Fellow at the EPFL Solar Energy Research Group (1981-1989); Research Fellow at the Applied Geophysics Institute of University of Lausanne (1980-1981).
Robert WestRobert West is a tenure-track assistant professor of computer science at EPFL, where he heads the Data Science Lab. In his research, he develops and applies techniques in machine learning, computational social science, natural language processing, social network analysis, and data mining. Bob also collaborates closely with the Wikimedia Foundation, in his role as a Wikimedia Research Fellow. Bob’s work has won several awards, including best/outstanding paper awards at ICWSM’21, ICWSM’19, and WWW’13, a best-paper runner-up award at WWW’16, a Google Faculty Research Award, a Facebook Research Award, a Hewlett-Packard Graduate Fellowship, and a Facebook Graduate Fellowship. He is actively involved in the research community, e.g., as an Associate Editor of ICWSM and EPJ Data Science and as a co-founder of the Wiki Workshop (held at WWW and ICWSM) and the Applied Machine Learning Days. Bob received his PhD in Computer Science from Stanford University, his MSc from McGill University, Canada, and his undergraduate degree from Technische Universität München, Germany.[Last updated: 25 Aug 2021]
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
Sahand Jamal RahiExpertise
- Biophysics- Statistical mechanics- Systems biology- Computational biology- Genetics
Teaching & PhD PhD Students Alisa Gross, Matthieu Schmidt, Marco Labagnara, Lorenzo Scutteri, Haozong Zeng Past EPFL PhD Students Ahmad Sadeghi, Mahsa Barzegarkeshteli, Vojislav Gligorovski, Roxane Oesterle Courses Biophysics : physics of biological systems PHYS-302 Understand and use the results and methods of population genetics, population dynamics, network theory, and reaction network dynami
