Panel 1
6G and AI: From Research Labs to Industry Deployment
(Organized by Keysight Technologies, Inc.)
Abstract: Groundbreaking ideas often demonstrate impressive results in controlled research environments but face significant challenges on the path to commercial deployment. Differences in hardware platforms, software ecosystems, scalability, reproducibility, regulatory requirements, and operational constraints frequently slow or prevent technology transfer. This panel brings together leaders from industry, government and academia to discuss how the wireless research community can better align experimental research with real-world needs. The panelists will debate the role of shared experimental infrastructure, open ecosystems, interpretability / explainability and reproducible experimentation in transforming research breakthroughs into technologies that power future 6G networks. Panelists will also explore lessons learned from deploying advanced communication, sensing, and AI-driven wireless systems, identify gaps in current research methodologies, and discuss the tools, platforms, and collaborations needed to accelerate the transition from laboratory prototypes to operational networks.
Panel 2
AI across the Stack - from PHY to Sky
(Organized by Ericsson)
Abstract: This panel will explore how artificial intelligence is becoming deeply embedded across the wireless stack, from physical-layer signal processing and RAN optimization to edge intelligence, network automation, and non-terrestrial networks. Furthermore, AI will be essential for managing highly dynamic propagation, mobility, spectrum, compute, and service orchestration across heterogeneous networks, enabling more seamless, resilient, and intelligent connectivity. The panel will examine how this tight integration can unlock new consumer experiences, reduce operational complexity, and create new revenue opportunities through AI-native services, distributed inference, personalized connectivity, and new classes of edge and satellite-enabled applications. It will also highlight emerging areas, such as integrated sensing and communications, AI-native receivers, autonomous network control, Physical AI, multi-modal edge intelligence, and large-scale NTN orchestration, where conventional model-based approaches can become too rigid or computationally prohibitive, and where learned methods may offer fundamentally new capabilities.