Workshop on Information Theory for Future Networks (IT-FuN)

We are happy to announce that the CEL will host an Information Theory Workshop at KIT on March 2-4, 2026. 
The workshop will feature invited talks from international experts and provide an opportunity to discuss recent advances and open challenges in information theory for communications. 
Specific topics of interest are:

Statistical Physics, Approximate Message Passing,  and their Applications in Communication 

Not least since Tanakas formula (link) the use of statistical physics methods has become an important part of the analysis of large scale communication systems. A comprehensive history of results is way beyond the scope of this short paragraph. However, a particularly important example is the Approximate Message Passing (AMP) algorithm. Having its roots in spin-glass research,  AMP found plenty of applications in information theory and is currently an active field of research.   

Recent developments in information theory for next-gen networks (Multiple-Access, URLLC, Non-Terrestrial Communication, Integrated Sensing and Communication) 

Emerging paradigms such as multiple-access for massive connectivity, ultra-reliable low-latency communication (URLLC) for mission-critical services, non-terrestrial communication (NTC) leveraging satellites and high-altitude platforms, and integrated sensing and communication (ISAC) for joint data transmission and environment perception pose new specification demands on wireless cellular systems. Recent advances in information theory provide new tools, bounds, and coding strategies to meet these demands, bridging theoretical limits with practical system design. 

Information Theory for Statistical Learning/The use of AI in Wireless Systems 

Information theory provides a powerful framework for understanding the fundamental limits of communication, representation, and inference, making it a natural foundation for statistical learning and modern AI applications. As wireless systems evolve toward higher capacity, lower latency, and greater adaptability, the integration of AI techniques guided by principles of information theory offers new opportunities to optimize resource allocation, enhance signal processing, and improve reliability under uncertainty. By bridging these two domains, researchers are developing intelligent wireless systems capable of learning from data, adapting to changing environments, and approaching theoretical performance limits, paving the way for next-generation communication networks.

Confirmed Speakers

Explore our confirmed speakers; stay tuned for additional outstanding contributors.

• Tobias Koch
• Gianluigi Liva
• Hamdi Joudeh
• Ramji Venkatramanan
• Giuseppe Durisi
• Gerhard Kramer
• Stephan ten Brink

Preliminary Workshop Program

We will have a three-day workshop. The tentative program is listed here:

Registration

Participation in the workshop is free of charge. However, registration is required. Registration will open soon—stay tuned!

Social Program

TBA