IZS 2026 Plenaries

Plenary Speakers

Jonas Peters, ETH Zurich
Igal Sason, Technion – Israel Institute of Technology
Pascal Vontobel, The Chinese University of Hong Kong

Plenary on Wednesday:
An Introduction to Causality and some Applications

Causal models can help us with the following two tasks:

1. they can, unlike statistical models, predict how a real-world system reacts under an active perturbation;
2. they suggest ways to robustly predict a response variable under a distribution shift, that is, in a scenario, where training and test distributions differ.

We introduce the concept of causal models and discuss principles allowing us to learn causal quantities from data. We highlight a few connections to information theory and, if time allows, mention some recent results on causal methodology and applications. No prior knowledge on causality is required.

Jonas is interested in using different types of data to predict the effect of interventions and to build statistical methods that are robust with respect to distributional shifts. He seeks to combine theory and methodology and tries to let real world applications guide his research. His work relates to areas such as causal inference, distribution generalization, dynamical systems, policy learning, graphical models, and independence testing. Since 2023, Jonas is professor in statistics at ETH Zurich. Previously, he has been a professor at the Department of Mathematical Sciences at the University of Copenhagen and a group leader at the Max-Planck-Institute for Intelligent Systems in Tuebingen. He studied Mathematics at the University of Heidelberg and the University of Cambridge and obtained his PhD jointly from MPI and ETH.

Plenary on Thursday:
Shannon Capacity of Graphs: Classical Results, Advances, and Open Problems

The Shannon capacity of a graph, introduced by Claude Shannon in 1956, is a central concept bridging zero-error information theory and graph theory. It characterizes the maximum rate of zero-error communication over a noisy channel when the channel is modeled by a graph whose vertices represent input symbols, and two vertices are adjacent if and only if the corresponding symbols can be confused by the channel with positive probability. This formulation reveals a deep and fundamental connection between zero-error communication problems and structural properties of graphs.

Determining the Shannon capacity of a graph is notoriously difficult, and exact values are known only for a limited number of graph families. Despite substantial progress over the past decades, many basic questions remain unresolved. One of the most prominent open problems is the determination of the Shannon capacity of odd cycle graphs of length greater than five.

In this talk, I will survey several classical results and discuss recent advances in the study of the Shannon capacity of graphs, with an emphasis on selected recent developments, including some joint work by the speaker. Several open problems will be highlighted as well.

Igal Sason received his B.Sc., Master, and Ph.D. degrees in electrical engineering from the Technion - Israel Institute of Technology in 1992, 1999, and 2001, respectively. From 1993 to 1997, he worked as an electrical engineer in Israel. Between 2001 and 2003, he was a scientific collaborator at the School of Computer and Communication Sciences at EPFL - Swiss Federal Institute of Technology, Lausanne, Switzerland. Since October 2003, he has been a faculty member at the Viterbi Faculty of Electrical and Computer Engineering of the Technion, where he is currently a professor and holds the Joseph and Bessie Feinberg Academic Chair. He has received several academic awards. Since October 2021, he has also held a secondary appointment as a professor in the Faculty of Mathematics at the Technion. His research focuses on information theory, coding theory, combinatoircs and graph theory.

Sason served in the editorial board of the IEEE Transactions on Information Theory for a total of ten years in various roles, including Associate Editor for Coding Theory, Associate Editor at Large, Executive Editor, and Editor-in-Chief. He also served as the Guest Editor of special issues on the mathematical foundations of information theory in the Entropy and the AIMS Mathematics journals. He is an IEEE Fellow of the Information Theory Society (since 2019), and a Fellow of the Institute of Combinatorics and its Applications (since 2024).

Plenary on Friday:
On Typical Permutations

Permutations play an important role in the design and analysis of many engineering systems and algorithms. This presentation will show that typical permutations play a key role when analyzing loopy-belief-propagation-based methods for approximating the permanent of a matrix consisting of non-negative-real-valued entries or complex-valued entries, in a similar way as typical sequences play an important role in information theory for analyzing data compression and reliable communication systems. Finally, the relevance of these permanent results for classical and quantum information processing systems will be discussed.

(Based on joint work with my MPhil/PhD students Yuwen Huang, Kit Shing Ng, Binghong Wu, and Junda Zhou.)

Pascal O. Vontobel received the Diploma degree in electrical engineering in 1997, the Post-Diploma degree in information techniques in 2002, and the Ph.D. degree in electrical engineering in 2003, all from ETH Zurich, Switzerland.

From 1997 to 2002 he was a research and teaching assistant at the Signal and Information Processing Laboratory at ETH Zurich, from 2006 to 2013 he was a research scientist with the Information Theory Research Group at Hewlett-Packard Laboratories in Palo Alto, CA, USA, and since 2014 he has been with the Department of Information Engineering at the Chinese University of Hong Kong, where, since 2023, he has been a (full) professor, department chairman, and graduate division head. Besides this, he was a postdoctoral research associate at the University of Illinois at Urbana-Champaign (2002-2004), a visiting assistant professor at the University of Wisconsin-Madison (2004-2005), a postdoctoral research associate at the Massachusetts Institute of Technology (2006), and a visiting scholar at Stanford University (2014). His research interests lie in information and coding theory, quantum information processing, data science, communications, and signal processing.

Dr. Vontobel was an Associate Editor for the IEEE Transactions on Information Theory (2009-2012), an Awards Committee Member of the IEEE Information Theory Society (2013-2014), a Distinguished Lecturer of the IEEE Information Theory Society (2014-2015), an Associate Editor for the IEEE Transactions on Communications (2014-2017), and a Thomas Cover Dissertation Awards Committee Member of the IEEE Information Theory Society (2023-2025). Moreover, he was / will be a TPC co-chair of the IEEE International Symposium on Information Theory (2016, 2027), the IEICE International Symposium on Information Theory and its Applications (2018), and the IEEE Information Theory Workshop (2018). He was the director of the Croucher Summer Courses in Information Theory (2021, 2023, 2025), co-organized several topical workshops, and was on the technical program committees of many international conferences. Furthermore, he was multiple times a plenary speaker at international information and coding theory conferences, he received an exemplary reviewer award from the IEEE Communications Society, and was awarded the ETH medal for his Ph.D. dissertation. He is an IEEE Fellow.

Back to the IZS 2026 home page.