Niccolo' DiscacciatiAfter receiving my Bachelor’s degree in Mathematical Engineering from Polytechnic University of Milan (PoliMi) in 2015, I took part in the double degree Master program between EPFL and PoliMi in Computational Science and Engineering. After an internship at the Swiss National Supercomputing Center, I joined the MCSS chair as a Master student in 2018 to write my thesis. Following graduation in 2018, I am currently pursuing my doctoral studies under the supervision of Prof. Hesthaven.
Rüdiger UrbankeRüdiger L. Urbanke obtained his Dipl. Ing. degree from the Vienna University of Technology, Austria in 1990 and the M.Sc. and PhD degrees in Electrical Engineering from Washington University in St. Louis, MO, in 1992 and 1995, respectively. He held a position at the Mathematics of Communications Department at Bell Labs from 1995 till 1999 before becoming a faculty member at the School of Computer & Communication Sciences (I&C) of EPFL. He is a member of the Information Processing Group. He is principally interested in the analysis and design of iterative coding schemes, which allow reliable transmission close to theoretical limits at low complexities. Such schemes are part of most modern communications standards, including wireless transmission, optical communication and hard disk storage. More broadly, his research focuses on the analysis of graphical models and the application of methods from statistical physics to problems in communications. From 2000-2004 he was an Associate Editor of the IEEE Transactions on Information Theory and he is currently on the board of the series "Foundations and Trends in Communications and Information Theory." In 2017 he was President of the Information Theory Society. From 2009 till 2012 he was the head of the I&C doctoral school, in 2013 he served as Dean a. i. of I&C, and since 2016 he is the Associated Dean for teaching of I&C. He is a co-author of the book "Modern Coding Theory" published by Cambridge University Press. Awards: 2021 IEEE Information Theory Society Paper Award 2016 STOC Best Paper Award 2014 La Polysphere Teaching Award 2014 IEEE Hamming Medal 2013 IEEE Information Theory Society Paper Award 2011 MASCO Best Paper Award 2011 IEEE Koji Kobayashi Award 2009 La Polysphere Teaching Award 2002 IEEE Information Theory Society Paper Award Fulbright Scholarship My students have won the following awards: M. Mondelli, 2021 IEEE Information Theory Paper Award M. Mondelli, EPFL Doctorate Award 2018 M. Mondelli, Patrick Denantes Award, 2017 M. Mondelli, IEEE IT Society Student Paper Award at ISIT, 2015 M. Mondelli, Dan David Prize Scholarship, 2015 H. Hassani, Inaugural Thomas Cover Dissertation Award, 2014 S. Kudekar, 2013 & 2021 IEEE Information Theory Paper Award A. Karbasi, Patrick Denantes Award, 2013 V. Venkatesan, Best Paper Award at MASCOTS, 2011 A. Karbasi, Best Student Paper Award at ICASSP, 2011 (with R. Parhizkar) A. Karbasi, Best Student Paper Award at ACM SIGMETRICS, 2010 (with S. Oh) S. Korada, ABB Dissertation Award, 2010 S. Korada, IEEE IT Society Student Paper Award at ISIT, 2009 (with E. Sasoglu) S. Korada, IEEE IT Society Student Paper Award at ISIT, 2008
William TrouleauAfter doing both a Bachelor and Master in Communication Systems at EPFL, I had the opportunity of working as an intern in the AI research lab of
Technicolor
in Los Altos, CA. The lab focuses on developing new analytics solutions in the areas of Human Behavior Modeling, Internet-Of-Things and wearable devices. I worked there for 9 months in 2014-2015 and developed a new generative mixture model to characterize the behavior of viewers on video-on-demand systems. Our approach enabled the predicting of future user actions (such as number of views and stopping time). This work lead to the publication
"Just One More: Modeling Binge Watching Behavior"
published in the 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) in August 2016.
Working in such a stimulating environment motivated me to continue my academic research. Therefore, I started my PhD at EPFL in September 2015. I received the EDIC Fellowship for my first year, and I am advised by
Pr. Patrick Thiran
and
Pr. Matthias Grossglauser
. My research revolves around the statistical and algorithmic aspects of learning causality structure from high-dimensional time series; with applications on epidemiology, public health, and information diffusion.
