CONFIRMED KEYNOTES
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Jakob Hoydis
Jakob Hoydis
Distinguished Research Scientist at NVIDIA
Jakob Hoydis is a Distinguished Research Scientist at NVIDIA working on the intersection of machine learning and wireless communications. Prior to this, he was Head of a research department at Nokia Bell Labs, France, and co-founder of the social network SPRAED. He obtained the diploma degree in electrical engineering from RWTH Aachen University, Germany, and the Ph.D. degree from Supéléc, France. From 2019-2021, he was chair of the IEEE COMSOC Emerging Technology Initiative on Machine Learning as well as Editor of the IEEE Transactions on Wireless Communications.
He is recipient of the 2019 VTG IDE Johann-Philipp-Reis Prize, the 2019 IEEE SEE Glavieux Prize, the 2018 IEEE Marconi Prize Paper Award, the 2015 IEEE Leonard G. Abraham Prize, the IEEE WCNC 2014 Best Paper Award, the 2013 VDE ITG Förderpreis Award, and the 2012 Publication Prize of the Supéléc Foundation. He has received the 2018 Nokia AI Innovation Award, as well as the 2018 and 2019 Nokia France Top Inventor Awards. He is a co-author of the textbook “Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency” (2017). He is a 2023 Distinguished Industry Speaker of the IEEE Signal Processing Society as well as an IEEE Fellow.
He is one of the maintainers and core developers of Sionna, a GPU-accelerated open-source link-level simulator for next-generation communication systems.
Keynote Title:
Keynote Title:
From Vision to Verification: Next-Gen Tools for 6G
From Vision to Verification: Next-Gen Tools for 6G
A key vision for 6G networks is their ability to autonomously adapt to the radio environments in which they operate. Advancing this vision requires flexible tools for building and executing digital twin networks that can be tailored to diverse research needs. In this talk, I will present a set of such tools developed at NVIDIA, demonstrating how hardware-accelerated real-time ray tracing and channel emulation enable the simulation of complete 5G networks in arbitrary environments on accessible devices. These capabilities let researchers test and validate new ideas under realistic and reproducible conditions, paving the way toward realizing the full potential of 6G innovation.
A key vision for 6G networks is their ability to autonomously adapt to the radio environments in which they operate. Advancing this vision requires flexible tools for building and executing digital twin networks that can be tailored to diverse research needs. In this talk, I will present a set of such tools developed at NVIDIA, demonstrating how hardware-accelerated real-time ray tracing and channel emulation enable the simulation of complete 5G networks in arbitrary environments on accessible devices. These capabilities let researchers test and validate new ideas under realistic and reproducible conditions, paving the way toward realizing the full potential of 6G innovation.
Vincent Deslandes
Vincent Deslandes
Strategic Project Manager & satellite telecommunications system architect at Kinéis
Dr. Vincent Deslandes is a satellite telecommunications system architect who earned a Ph.D. in 2012 from the University of Toulouse in collaboration with IRIT laboratory Toulouse and Airbus Defense and Space, whose topic was already about the integration of 4G satellite & terrestrial communication systems. He has worked 15 years at Airbus Defence & Space on the design and optimization of advanced satellite networks, among which LEO, GEO, mobile and IoT systems. With a background in telecommunication & system engineering, Dr Deslandes has contributed to groundbreaking projects in particular on satellite IoT with the design of a full IoT protocol deployed on Astrocast network and with next generation 5G NTN Nb-IoT networks. He is now in charge of R&D at Kinéis, a satcom IoT operator currently deploying an IoT service based on a constellation of 25 LEO satellites.
Keynote Title:
Keynote Title:
Is the democratisation of satcoms truly underway?
Is the democratisation of satcoms truly underway?
In recent years, we have witnessed an ongoing revolution in the world of satellite communications (satcom): the democratisation of satellite connectivity for the general public—far beyond satellite television, which is experiencing a slow but certain decline. The emergence of mega-constellations (led by Starlink) providing cheap and efficient internet access—soon followed by mobile communications—will allow anyone to connect via an ever-growing and increasingly efficient network of satellites. The standardisation of Non-Terrestrial Networks (NTN) in the 5G standard is building a bridge between the traditional mobile market and the satellite communications market (which is 100 to 1000 times smaller). As a result, a myriad of satellite network solutions (terminal modems, base stations, core networks) are now available “off the shelf”, interoperable with each other and with terrestrial networks. However, space remains a hostile environment, difficult to reach, and many challenges still need to be overcome before satellite communications become truly accessible from everyone’s pocket. In order to highlight this difficult question, this keynote will constitute an introduction to satellite communication networks and provide a status of the satcom market, its current trends and challenges.
Laurent Toutain
Laurent Toutain
Professor at IMT Atlantique
Laurent Toutain has been a professor at IMT Atlantique since 1991, specializing in network protocols and the Internet of Things (IoT). He holds a Ph.D. in computer science and is internationally recognized as an expert in data compression for highly constrained networks. He has contributed to seven IETF standardization RFCs, notably on SCHC (Static Context Header Compression), a key technology for optimizing IoT communications.
In 2016, he co-founded Acklio, a startup based on his research in IoT interoperability. Laurent Toutain remains active in IETF working groups, helping to shape Internet standards. His current research focuses on integrating compression solutions into 5G networks and Industry 4.0 applications.
Keynote Title:
Keynote Title:
From Verbose to Efficient: Optimizing Data Models for Resource-Constrained IoT Systems
From Verbose to Efficient: Optimizing Data Models for Resource-Constrained IoT Systems
The adoption of the Internet of Things (IoT) has not reached the anticipated levels despite significant potential and market growth. One of the primary barriers to widespread IoT deployment is the lack of interoperability (the inability of heterogeneous devices from different manufacturers to communicate and share data seamlessly). This fragmentation results in costly custom integrations, increased deployment and operational complexity, and ultimately higher total cost of ownership. Enabling true interoperability is essential, reducing system complexity, and lowering costs through standardized communication protocols and data representations among diverse devices and platforms.
The adoption of the Internet of Things (IoT) has not reached the anticipated levels despite significant potential and market growth. One of the primary barriers to widespread IoT deployment is the lack of interoperability (the inability of heterogeneous devices from different manufacturers to communicate and share data seamlessly). This fragmentation results in costly custom integrations, increased deployment and operational complexity, and ultimately higher total cost of ownership. Enabling true interoperability is essential, reducing system complexity, and lowering costs through standardized communication protocols and data representations among diverse devices and platforms.
At the heart of this challenge lies the need for universal data models—standardized representations of information that allow different systems to understand and exchange data consistently. Traditional approaches to defining such data models rely on verbose, text-based formats that encode significant metadata and structural information alongside the actual data. While these formats ensure clarity and ease of human interpretation, they are inefficient for resource-constrained IoT environments where bandwidth, energy, and computational power are severely limited. This inefficiency becomes particularly problematic as IoT deployments scale across millions of interconnected devices.
At the heart of this challenge lies the need for universal data models—standardized representations of information that allow different systems to understand and exchange data consistently. Traditional approaches to defining such data models rely on verbose, text-based formats that encode significant metadata and structural information alongside the actual data. While these formats ensure clarity and ease of human interpretation, they are inefficient for resource-constrained IoT environments where bandwidth, energy, and computational power are severely limited. This inefficiency becomes particularly problematic as IoT deployments scale across millions of interconnected devices.
Recent advances in data compression and encoding techniques offer a promising solution. Specifically, binary encoding combined with header compression can dramatically reduce message sizes while preserving the semantic meaning and machine-processable structure of the data. These compressed representations enable efficient communication over bandwidth-limited networks, reduce energy consumption on battery-powered devices, and decrease the computational overhead required for message processing. Such improvements are critical for enabling scalable, cost-effective IoT deployments in constrained environments—from sensor networks in remote locations to edge computing systems in smart cities and industrial facilities.
Recent advances in data compression and encoding techniques offer a promising solution. Specifically, binary encoding combined with header compression can dramatically reduce message sizes while preserving the semantic meaning and machine-processable structure of the data. These compressed representations enable efficient communication over bandwidth-limited networks, reduce energy consumption on battery-powered devices, and decrease the computational overhead required for message processing. Such improvements are critical for enabling scalable, cost-effective IoT deployments in constrained environments—from sensor networks in remote locations to edge computing systems in smart cities and industrial facilities.
This presentation will show how modern compression and encoding techniques can transform IoT interoperability. By combining standardized data models with compact binary formats, we can achieve robust, vendor-neutral communication and the efficiency needed for large-scale, affordable IoT systems.
This presentation will show how modern compression and encoding techniques can transform IoT interoperability. By combining standardized data models with compact binary formats, we can achieve robust, vendor-neutral communication and the efficiency needed for large-scale, affordable IoT systems.
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