Fields of expertise
BiographyPatrick 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.
Current and recent workWireless and PLC networks: scaling laws, MAC performance. Network loss tomography. Random gossip algorithms. Source location of epidemics. Mobility data mining and population sampling. Patrick Thiran
Leveraging Unlabeled Data to Track Memorization2023-05-01. 11th International Conference on Learning Representations (ICLR 2023), Kigali, Rwanda, May 1-5, 2023.
Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed InferenceLausanne, EPFL, 2023. DOI : 10.5075/epfl-thesis-9868.
Momentum-Based Policy Gradient with Second-Order Information2022-12-20.
Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function2022-09-14.
Disparity Between Batches as a Signal for Early Stopping2021-09-13. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), Bilbao, Basque Country, Spain, September 13-17, 2021. DOI : 10.1007/978-3-030-86520-7_14.
Sequential metric dimension for random graphsJournal of Applied Probability. 2021. DOI : 10.1017/jpr.2021.16.
A Registration Method for Three-Dimensional Analysis of Bone Mineral Density in the Proximal TibiaJournal Of Biomechanical Engineering-Transactions Of The Asme. 2021-01-01. DOI : 10.1115/1.4048335.
A Variational Inference Approach to Learning Multivariate Wold Processes2021. 24th International Conference on Artificial Intelligence and Statistics (AISTATS), San Diego, California, USA, April 13-15, 2021.
Learning Hawkes Processes Under Synchronization Noise2019-06-09. 36th International Conference on Machine Learning, Long Beach, California, USA, June 9-15, 2019. p. 6325--6334.
A User Study of Perceived Carbon Footprint2019. Climate Change Workshop at NeurIPS, Vancouver, BC, Canada, December 8-14, 2019.
Learning Hawkes Processes from a Handful of Events2019. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, December 8-14, 2019.
On the Delays in Time-Varying Networks: Does Larger Service-Rate Variance Imply Larger Delays?2018-06-25. Eighteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing, Los Angeles, CA, USA, June 26 - 29, 2018. p. 201-210. DOI : 10.1145/3209582.3209603.
Coordinate Descent with Bandit Sampling2018-01-01. 32nd Conference on Neural Information Processing Systems (NIPS), Montreal, CANADA, Dec 02-08, 2018.
Optimal Number of Paths with Multipath Routing in Hybrid Networks2018-01-01. 19th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Chania, GREECE, Jun 12-15, 2018. DOI : 10.1109/WoWMoM.2018.8449781.
Optimal Number of Paths with Multipath Routing in Hybrid Networks2018
Csma/ca in time and frequency domainsUS10321488 ; US2017347377 . 2017.
How CSMA/CA With Deferral Affects Performance and Dynamics in Power-Line CommunicationsIeee-Acm Transactions On Networking. 2017. DOI : 10.1109/Tnet.2016.2580642.
Analysis and Enhancement of CSMA/CA With Deferral in Power-Line CommunicationsIEEE Journal on Selected Areas in Communications. 2016. DOI : 10.1109/Jsac.2016.2566078.
Electri-Fi Your Data: Measuring and Combining Power-Line Communications with WiFi (Technical Report 210617, EPFL)2015
Introduction aux sciences de l'informationLausanne: Presses Polytechniques et Universitaires Romandes.
Virtually Moving Base Stations for Energy Efficiency in Wireless Sensor Networks2015
Method, apparatus and computer program product for locating a source of diffusion in a networkUS2014129190 . 2014.
Method to optimize the communication parameters between an access point and at least one client deviceUS9549328 ; US2014307571 . 2014.
On the MAC for Power-Line Communications: Modeling Assumptions and Performance Tradeoffs (Technical Report 205771, EPFL)2014
Simulator and Experimental Framework for the MAC of Power-Line Communications2014
Mitigating Epidemics through Mobile Micro-measures2013. NetMob, Boston, Massachusetts, USA, May 2013.
Where to go from here? Mobility prediction from instantaneous informationPervasive And Mobile Computing. 2013. DOI : 10.1016/j.pmcj.2013.07.006.
Wireless Multi-hop Networks Beyond Capacity2013. 19th IEEE International Workshop on Local and Metropolitan Area Networks (LANMAN). DOI : 10.1109/LANMAN.2013.6528289.
SAW: Spectrum Assignment for WLANs2013. ACM S3 2013, Miami, Florida, USA, September 30, 2013.
Scalable Routing Easy as PIE: a Practical Isometric Embedding Protocol (Technical Report)2013
Automatic Mallampati Classification Using Active Appearance Models2012. International Workshop on Pattern Recognition for Healthcare Analytics, Tsukuba Science City, Japan, November 11, 2012.
|P. Pinto, P. Thiran and M. Vetterli
Physical Review Letters, vol. 109, num. 068702, 2012
|Locating the Source of Diffusion in Large-Scale Networks|
|V. Etter, M. Grossglauser and P. Thiran
Proceedings of the first ACM conference on Online Social Networks (COSN'13)
|Launch Hard or Go Home! Predicting the Success of Kickstarter Campaigns|
|F. Movahedi Naini, O. Dousse, P. Thiran and M. Vetterli
Proc. ISIT, Saint-Petersburg, Russia, 2011.
|Population Size Estimation Using a Few Individuals as Agents|
|F. B�n�zit, P. Thiran and M. Vetterli
IEEE Journal of Selected Topics in Signal Processing, vol. 5(4), p. 791-804, 2011.
|The Distributed Multiple Voting Problem|
|A. Aziz, D. Starobinski and P. Thiran
IEEE/ACM Transactions on Networking, vol. 19(4), Aug. 2011
|Understanding and Tackling the Root Causes of Instability in Wireless Mesh Networks|
|D. Ghita, H. Nguyen, M. Kurant, K. Argyraki and P. Thiran
Proc. IEEE Infocom, San Diego, CA, 2010.
|Netscope: Practical Network Loss Tomography|
|M. Durvy, O. Dousse and P. Thiran
IEEE Journal on Selected Areas in Communications, vol. 27(7), pp. 1093-1104, 2009.
|On the Fairness of Large CSMA Networks|
|M. Kafsi, M. Grossglauser and P. Thiran
IEEE Transactions on Information Theory, vol. 59(9), pp. 5577 - 5583, 2013
|The Entropy of Conditional Markov Trajectories|
Teaching & PhD