Program

In recent years, synthetic molecular communications (MC) has emerged as a new field of research in information theory and communication engineering with strong links to several other disciplines, including biology, nanotechnology, and medicine. MC is expected to provide connectivity in environments that are not suitable for conventional communication systems based on electromagnetic (EM) waves, such as the human cardiovascular system, bio-processes, and water pipes, and facilitate novel applications such as the Internet of BioNanoThings (IoBNT), targeted drug delivery, and interfacing with animals and plants.

Although some concepts known from conventional communication systems are applicable in MC, there are also many new aspects and differences. In this tutorial, we will first provide a broad introduction to synthetic MC, reviewing different forms of MC occurring in nature, the propagation of molecules, and potential applications. Subsequently, we will introduce communication-theoretical models for MC channels, discuss phenomena such as degradation and dispersion, and unveil concepts for MC system design. Finally, we will present an overview of state-of-the-art experimental MC systems and provide case studies for applications of MC concepts, including bio-process control and olfactory systems.

The rise of machine learning has introduced powerful generative models, including diffusion models, which have achieved remarkable success in areas like image generation. In this talk, we provide a comprehensive overview of diffusion models, explaining their underlying mechanisms and their potential in tackling complex problems. We then explore how these models can be applied to wireless communications to address critical challenges such as channel estimation and reliable data transmission over low-SNR (Signal-to-Noise Ratio) links. By leveraging diffusion models’ ability to incorporate prior knowledge about data distributions, we demonstrate how they can significantly enhance transmission accuracy and efficiency in wireless systems. Experimental results will be presented to showcase the performance improvements achieved using these models, particularly in scenarios where traditional methods struggle. Finally, we will outline key challenges and promising research directions in integrating diffusion models with next-generation wireless technologies.

Large-scale MIMO communication (at sub-6GHz, mmWave, and sub-THz bands) is a key enabler for 5G, 6G, and beyond. Scaling MIMO systems, however, is subject to critical challenges, such as the large channel acquisition and beam training overhead and the sensitivity to channel estimation errors (especially at lower frequencies) and blockages (at higher frequencies). These challenges make it difficult for MIMO systems to support applications that have high mobility and strict reliability constraints. In this talk, I will first motivate the use of machine learning and sensory data to address these challenges. Then, I will present a few key machine-learning roles, enabling datasets, and recent hardware proof-of-concept prototypes that demonstrate the machine-learning gains in real-world environments.

Since the seminal work of Shor we know that efficient quantum computers are a threat to the security of public-key cryptography that is currently deployed. A huge amount of work is being put into developing an efficient quantum computer. But even if the advent of such a computer may wait for decades, it is urgent to deploy post-quantum cryptography (PQC), i.e: cryptographic solutions working on our devices which are secure even against « quantum adversaries ». Indeed, an attacker could store encrypted sessions and wait until a quantum computer is available to decrypt. In this context the National Institute of Standard Technology (NIST) has launched in 2017 a call for standardizing public-key PQC schemes. We are currently in the final step of the standardization and most of the selected solutions are basing their security on the hardness of error correcting code problems (but also on hard Euclidean lattice problems). The aforementioned problems come from information theory, which has proven to be an amazing source of hard problems. The most famous is likely the decoding problem: given a code and a target, the goal is to find the closest codeword (in terms of Hamming distance). This problem is considered particularly hard when no structure is assumed for the code, especially when the code is assumed to be random. Surprisingly, since ’78, with the work of McEliece and later Alekhnovich in ’03, we know how to construct cryptographic solutions whose security is based on the difficulty of this problem and which turn out to be secure even against quantum adversaries (at least in our current knowledge). The field studying how to build cryptographic solutions via the hardness of decoding a random code is referred to as code-based cryptography.
The aim of this talk will be to present how we can achieve security via the hardness of the decoding problem of a random code. Then in a last part, we will introduce the basics of quantum computing and explain why it poses a threat to the security of currently deployed cryptographic primitives but not to code-based cryptography.

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The integration of radio communication and sensing services in the same network infrastructure will be a key feature of next-generation wireless technology. This emerging paradigm, known as joint communication and sensing (JCAS) or integrated sensing and communication (ISAC), will enable future wireless base-stations to communicate with active devices, and simultaneously sense their surroundings; all using the same spectrum and hardware resources. Realizing provably efficient and reliable JCAS systems, however, strongly hinges on developing an information-theoretic framework through which we can establish fundemental performance limits and trade-offs, and derive insights into the design of optimal JCAS schemes. In this talk, I will discuss recent progress and steps towards an information theory for JCAS systems.

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The scientific community and industry are exploring ways to meet the increasing traffic demand in optical networks at various levels. While technological innovations aim to expand bandwidth and spatial multiplexing through the development of new fibers and optical amplifiers, advancements in modulation techniques, coding, and signal processing are being pursued to maximize spectral efficiency to fully leverage the capacity of existing fiber links. The challenge is further complicated—and made more intriguing—by the nonlinearity of optical fibers, which make the determination of channel capacity an open problem. In this talk, I will introduce the problem of fiber optic channel capacity and discuss recent techniques proposed to evaluate it and to practically approach it through advanced modulation strategies. Specifically, I will focus on a novel method called sequence selection. Originally developed as a tool in information theory to derive capacity bounds, sequence selection also shows promise as a practical and general method for the implementation of efficient modulation schemes, allowing more reliable data transmission over existing fiber networks.

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Dr. Samad Ali received his Ph.D. in Wireless Communications Engineering from the University of Oulu, Finland. He is currently a Senior Research Specialist at Nokia and an Adjunct Professor (Docent) at the University of Oulu. His primary research interests lie in the applications of artificial intelligence and machine learning (AI/ML) in wireless communication networks.

Ahmed Alkhateeb received his B.S. and M.S. degrees in Electrical Engineering from Cairo University, Egypt, in 2008 and 2012, and his Ph.D. degree in Electrical Engineering from The University of Texas at Austin, USA, in 2016. After the Ph.D., he spent some time as a Wireless Communications Researcher at the Connectivity Lab, Facebook, before joining Arizona State University (ASU) in the Spring of 2018, where he is currently an Associate Professor in the School of Electrical, Computer, and Energy Engineering.

His research interests are in the broad areas of wireless communications, signal processing, machine learning, and applied math. Dr. Alkhateeb is the recipient of the 2012 MCD Fellowship from The University of Texas at Austin, the 2016 IEEE Signal Processing Society Young Author Best Paper Award for his work on hybrid precoding and channel estimation in millimeter-wave communication systems, and the NSF CAREER Award 2021 to support his research on leveraging machine learning for large-scale MIMO systems.

Thomas Debris-Alazard is a research scientist (chargé de recherche) at Inria in the Grace project team and part-time assistant professor at École Polytechnique where he teaches information theory and quantum computing. He received his Ph.D. at Inria in Paris Sorbonne Université for which he got the Gilles Khan Ph.D award. His research interests are code- and lattice-based cryptography but also in the areas of quantum computing.

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Hamdi Joudeh is an Associate Professor in the Department of Electrical Engineering at the Eindhoven University of Technology, The Netherlands. He received his Ph.D. in Electrical Engineering and M.Sc. in Communications and Signal Processing from Imperial College London, UK, in 2016 and 2011 respectively. His research interests are in the areas of Information Theory and Wireless Communications. He was awarded a starting grant from the European Research Council (ERC) in 2023.

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Robert Schober (S’98, M’01, SM’08, F’10) received the Diplom (Univ.) and the Ph.D. degrees in electrical engineering from Friedrich-Alexander University of Erlangen-Nuremberg (FAU), Germany, in 1997 and 2000, respectively. From 2002 to 2011, he was a Professor and Canada Research Chair at the University of British Columbia (UBC), Vancouver, Canada. Since January 2012 he is an Alexander von Humboldt Professor and the Chair for Digital Communication at FAU. His research interests fall into the broad areas of Communication Theory, Wireless and Molecular Communications, and Statistical Signal Processing.

Robert received several awards for his work including the 2002 Heinz Maier Leibnitz Award of the German Science Foundation (DFG), the 2004 Innovations Award of the Vodafone Foundation for Research in Mobile Communications, a 2006 UBC Killam Research Prize, a 2007 Wilhelm Friedrich Bessel Research Award of the Alexander von Humboldt Foundation, the 2008 Charles McDowell Award for Excellence in Research from UBC, a 2011 Alexander von Humboldt Professorship, a 2012 NSERC E.W.R. Stacie Fellowship, a 2017 Wireless Communications Recognition Award by the IEEE Wireless Communications Technical Committee, and the 2022 IEEE Vehicular Technology Society Stuart F. Meyer Memorial Award. Furthermore, he received numerous Best Paper Awards including the 2022 ComSoc Stephen O. Rice Prize and the 2023 ComSoc Leonard G. Abraham Prize. Since 2017, he has been listed as a Highly Cited Researcher by the Web of Science. Robert is a Fellow of the Canadian Academy of Engineering, a Fellow of the Engineering Institute of Canada, and a Member of the German National Academy of Science and Engineering (acatech).

He served as Editor-in-Chief of the IEEE Transactions on Communications, VP Publications of the IEEE Communication Society (ComSoc), ComSoc Member at Large, and ComSoc Treasurer. Currently, he serves as Senior Editor of the Proceedings of the IEEE and as ComSoc President.

Marco Secondini received the M.S. degree in Electrical Engineering from the University of Roma Tre, Rome, Italy, in 2000, and the Ph.D. degree from Scuola Superiore Sant’Anna, Pisa, Italy, in 2006. In 2005, he was a Visiting Faculty Research Assistant with the Photonics Group, University of Maryland Baltimore County, Baltimore, USA. Since 2007, he has been with Scuola Superiore Sant’Anna, where he currently serves as an Associate Professor of Telecommunications. He also collaborates with the Photonic Networks & Technologies National Lab of the CNIT in Pisa. He served as Associate Editor for IEEE Transactions on Communications, Guest Editor for IEEE Journal on Selected Areas in Communications, and as TPC member of major conferences on optical communications. His research interests are in the area of optical fiber communications, with a special focus on information theoretical aspects, channel modelling, modulation and detection techniques, signal processing. In this area, he has coauthored more than 140 papers in leading journals and conferences.

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