Matthias Grossglauser
EPFL IC IINFCOM INDY1
INF 015 (Bâtiment INF)
Station 14
1015 Lausanne
+41 21 693 26 21
+41 21 693 81 16
Office: INF 015
EPFL › IC › IINFCOM › INDY1
Website: https://indy.epfl.ch/
EPFL IC IINFCOM INDY1
INF 015 (Bâtiment INF)
Station 14
1015 Lausanne
+41 21 693 81 16
Office: INF 015
EPFL › IC › IC-SSC › SSC-ENS
Website: https://ssc.epfl.ch
EPFL IC IINFCOM INDY1
INF 015 (Bâtiment INF)
Station 14
1015 Lausanne
+41 21 693 81 16
Office: INF 015
EPFL › IC › IC-SIN › SIN-ENS
Website: https://sin.epfl.ch
- Matthias Grossglauser is a Professor of Computer and Communication Sciences at EPFL in Lausanne, Switzerland, where he co-directs the Information and Network Dynamics lab. His current research interests center on machine learning, stochastic networks, and discrete choice models, and on their applications in artificial intelligence, reinforcement learning, network science, computational social sciences, and recommender systems. He is also a member of the Federal Communications Commission (ComCom), the independent regulatory authority for the Swiss telecommunications market.
- He was the director of EPFL's Doctoral School in Computer and Communication Sciences (2016-2019). From 2007-2010, he was with the Nokia Research Center (NRC) in Helsinki, Finland, leading the Internet Laboratory, a research organization comprising seven teams in security, networking, social media, and user experience, and served on Nokia's CEO Technology Council, a team of technology experts advising the Nokia CEO. Prior to this, he was Assistant Professor at EPFL, and Principal Research Scientist in the Networking and Distributed Systems Laboratory at AT&T Research (Shannon Labs) in New Jersey, USA. He holds a Ph.D. degree in Computer Science from Sorbonne Universités, a M.Sc. degree in Electrical Engineering from Georgia Institute of Technology, and an engineering degree in Communication Systems from EPFL. He is a Fellow of the IEEE and of ELLIS, and the recipient of the 1998 Cor Baayen Award from the European Research Consortium for Informatics and Mathematics (ERCIM) and of the 2006 CoNEXT/SIGCOMM Rising Star Award.
Awards
Cor Baayen Award
ERCIM
1998
CoNEXT/SIGCOMM Rising Star Award
0
IEEE Fellow
IEEE
2021
Infoscience
Locating Mobile Nodes with EASE: Learning Efficient Routes from Encounter Histories Alone
IEEE/ACM Transactions on Networking. 2006. DOI : 10.1109/TNET.2006.876204.On information transmission over a finite buffer channel
IEEE Transactions on Information Theory. 2006. DOI : 10.1109/TIT.2005.864445.Mobility Increases the Capacity of Ad Hoc Wireless Networks
IEEE/ACM Transactions on Networking. 2002. DOI : 10.1109/TNET.2002.801403.Trajectory Sampling for Direct Traffic Observation
IEEE/ACM Transactions on Networking. 2001. DOI : 10.1109/90.929851.Teaching & PhD
PhD Students
Daichi Kuroda, Oscar Villemaud, Mohammadsadegh Khorasani, Amir Mohammad Aboueimehrizi
Past EPFL PhD Students
Michal Piorkowski, Natasa Sarafijanovic-Djukic, Pedram Pedarsani, Mohamed Kafsi, Vincent Etter, Ehsan Kazemi, Lyudmila Yartseva, Young Jun Ko, Lucas Maystre, William Trouleau, Daniyar Chumbalov, Aswin Suresh
Past EPFL PhD Students as codirector
Henri Dubois-Ferrière, Dominique Florian Tschopp, Victor Kristof
Courses
Internet analytics
COM-308
Internet analytics is the collection, modeling, and analysis of user data in large-scale online services, such as social networking, e-commerce, search, and advertisement. This class explores a number of the key functions of such online services that have become ubiquitous over the past decade.
Networks out of control
COM-512
The goal of this class is to acquire mathematical tools and engineering insight about networks whose structure is random, as well as learning and control techniques applicable to such network data.
Principles of online decision-making
CS-303
This course provides a mathematical treatment of online decision-making. It covers bandits (multi-armed, contextual, structured), Markov Decision Processes (MDPs), and related topics. Key concepts include exploration-exploitation, UCB, Thompson sampling, and tools to derive regret bounds.