Rüdiger Urbanke

coding, communications, information theory, graphical models, methods of statistical physics applied to problems in communications and computer science

Biography

Rüdiger 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:

2023 Claude E. Shannon Award
2023 IEEE Leon K. Kirchmayer Graduate Teaching Award
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 MASCOT 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

CONTACT

Secretariat

Muriel Bardet
Building INR 137
Station 14
CH-1015 Lausanne

Tel. 41 21 693 76 95
muriel.bardet@epfl.ch

OTHER PUBLICATIONS

List

CURRENT WORK

Many interesting problems in communications and computer science can be phrased as inference problems on sparse graphical models.

I am studying the behavior of such systems as a function of underlying parameters (phase transitions) as well as trying to find efficient algorithms to solve fundamental tasks related to such systems. Message-passing algorithms as well as methods from statistical physics play an important role in my research.

Rüdiger Urbanke

Publications

Infoscience publications

Infoscience

Modern Coding Theory

T. Richardson; R. Urbanke

Cambridge University Press.

Detailed record

The Capacity of Low-Density Parity Check Codes under Message-Passing Decoding

T. Richardson; R. Urbanke

IEEE Transactions on Information Theory. 2001. DOI : 10.1109/18.910577.

Detailed record

Design of capacity-approaching irregular low-density parity-check codes

T. Richardson; A. Shokrollahi; R. Urbanke

IEEE Transactions on Information Theory. 2001. DOI : 10.1109/18.910578.

Detailed record

Teaching & PhD

Teaching

Communication Systems

Computer Science

PhD Students

Abdelhadi Dina Khaled Sayed, Gluch Grzegorz Adam, Maggiori Andreas, Weinberger Thomas Helmut,

Past EPFL PhD Students

Ajdari Rad Ali , Aref Vahid , El-Khatib Rafah , Giurgiu Andrei , Hassani Seyed Hamed , Ivanov Kirill , Karbasi Amin , Korada Satish Babu , Kudekar Shrinivas , Liu Wei , Mitrovic Slobodan , Mondelli Marco , Neuberg Christine , Venkatesan Vinodh , Vuffray Marc ,

Courses

Foundations of Data Science

We discuss a set of topics that are important for the understanding of modern data science but that are typically not taught in an introductory ML course. In particular we discuss fundamental ideas and techniques that come from probability, information theory as well as signal processing.

Statistical Physics for Communication and Computer Science

The course introduces the student to notions of statistical physics which have found applications in communications and computer science. We focus on graphical models with the emergence of phase transitions, and their relation to the behavior of efficient algorithms.

Learning theory

Machine learning and data analysis are becoming increasingly central in many sciences and applications. This course concentrates on the theoretical underpinnings of machine learning.

Online People Directory

Rüdiger Urbanke

Full Professor

Fields of expertise

Biography

CONTACT

OTHER PUBLICATIONS

CURRENT WORK

Publications

Infoscience publications

Infoscience

Modern Coding Theory

The Capacity of Low-Density Parity Check Codes under Message-Passing Decoding

Design of capacity-approaching irregular low-density parity-check codes

Teaching & PhD

Teaching

PhD Students

Past EPFL PhD Students

Courses

Foundations of Data Science

Statistical Physics for Communication and Computer Science

Learning theory

All postal addresses and positions