Future WINE 2026

Invited Speakers

Meet the invited speakers and join the Future WINE 2026 event.

October 26 · Keynote Session

Prof. Tarik Taleb

Ruhr University Bochum, Germany

Session: Keynote Session
Time: 13:30–15:00, October 26

Talk title

Advancing AI-Native Orchestration Across the Cloud-Edge-Extreme Edge Continuum

Abstract

The convergence of cloud, edge, and extreme-edge computing is reshaping distributed infrastructures, enabling a new generation of intelligent, latency-sensitive, and mission-critical applications. However, orchestrating heterogeneous resources and services across this highly dynamic, multi-domain continuum introduces significant challenges in scalability, adaptability, mobility, and resilience. This talk introduces MIRO, an AI-native orchestration framework that leverages advanced reasoning models, large language models (LLMs), and predictive analytics to automate resource management and the end-to-end service lifecycle, including deployment, adaptation, migration, and security. Building on MIRO's capabilities, the talk explores the evolution towards Extreme Edge Orchestration, extending intelligence and orchestration capabilities to highly distributed, resource-constrained, and potentially mobile devices. Particular emphasis is placed on decentralized decision-making, context-aware adaptation, and collaborative intelligence across the continuum. The talk concludes with a vision for unified, autonomous, and resilient AI-native orchestration as a key enabler of next-generation 6G services and applications.

Biography

Tarik Taleb is a Full Professor at Ruhr University Bochum, Germany, where he heads the Institute for Networked Energy-Efficient Systems. He is also the founder of the MOSA!C Lab, a research laboratory dedicated to pioneering technologies for next-generation networks and intelligent distributed systems. Previously, he served as a Professor at the Centre for Wireless Communications, University of Oulu, Finland, and as an Associate Professor at Aalto University, Finland. Earlier in his career, he held positions as a Senior Researcher and 3GPP Standards Expert at NEC Europe, contributing to the standardization of the Evolved Packet System (EPS), and as an Assistant Professor at Tohoku University, Japan. He received his B.E., M.S., and Ph.D. degrees in Information Sciences from Tohoku University in 2001, 2003, and 2005, respectively. Prof. Taleb is internationally recognized for his contributions to mobile networking, network softwarization, edge and cloud computing, and intelligent network management. His research has been instrumental in advancing mobile core network architectures, network slicing, multi-domain orchestration, software-defined security, and end-to-end service lifecycle management. His current research focuses on AI-native network and service orchestration, leveraging large language models, advanced AI reasoning, and predictive intelligence to enable autonomous, adaptive, secure, and resilient infrastructures across the cloud–edge continuum, including the extreme edge. Bridging fundamental research, industrial innovation, and international standardization, Prof. Taleb continues to advance the vision of self-managing, AI-native, and energy-efficient networked systems, laying the foundations for next-generation 6G networks and intelligent distributed services.

October 26 · Technical Session

Prof. Yuto Lim

JAIST, Japan

Session: AI-Wireless Session
Time: 15:10–16:10, October 26

Talk title

What Will Future AI-Driven Wireless Networks Look Like?

From Intelligent Decisions to Adaptive, Collaborative, and Explainable Networks

Abstract

Artificial intelligence (AI) is increasingly becoming an integral part of future wireless networks, moving beyond conventional performance optimization toward autonomous and adaptive network intelligence. In this talk, I explore this evolution through several of our recent studies on AI-assisted wireless networking. First, I discuss how multiple AI techniques can work together for network decision-making, where a Broad Learning System (BLS) performs intelligent server allocation while Q-learning determines interference-aware multihop communication paths. This demonstrates how different learning mechanisms can play complementary roles in solving interconnected wireless-network problems. Second, I extend this perspective from network decision-making to network adaptation through AI-assisted mobile edge computing (MEC) placement, where learning and optimization are combined to rapidly determine suitable edge-resource locations under dynamic wireless environments and time constraints. Finally, I broaden the discussion toward distributed network intelligence through federated learning for vehicular localization, where devices collaboratively learn without centralizing their local data and explainable AI is incorporated into the aggregation process. Through these examples, I present a progressive view of future AI-driven wireless networks in which AI not only decides, but also adapts, learns collaboratively, and ultimately explains its decisions.

Biography

Yuto Lim received the B.Eng. (Hons.) and M.Inf.Tech. degrees from Universiti Malaysia Sarawak (UNIMAS), Malaysia, in 1998 and 2000, respectively, and the Ph.D. degree in communications and computer engineering from Kyoto University, Japan, in 2005. From November 2005 to September 2009, he was an Expert Researcher with the National Institute of Information and Communications Technology (NICT), Japan. In October 2009, he joined the Japan Advanced Institute of Science and Technology (JAIST), Japan, where he served as an Associate Professor until March 2025 and has been a Full Professor since April 2025. His research interests include future wireless communications and networks, AI-driven wireless networking, wireless multihop networks, mobile edge computing, the Internet of Things (IoT), cyber-physical systems, and quantum networks. His current research particularly explores the integration of artificial intelligence and networking technologies toward intelligent, adaptive, and autonomous future communication systems. He is a member of the IEEE, IEICE, and IPSJ.

October 26 · Technical Session

Dr. Cuiwei He

JAIST, Japan

Session: OWC Session
Time: 16:10–17:10, October 26

Talk title

Advanced Receiver Technologies for Next-Generation Optical Wireless Communications

Abstract

Optical wireless communication (OWC) is expected to augment existing RF networks in future 6G wireless systems. The transmission performance of an OWC system highly depends on the design of the optical receiver. This talk will cover several emerging research topics related to OWC receivers, including fluorescent antennas, highly sensitive photon-counting detectors, and photonic reservoir computing for signal processing.

Biography

Cuiwei He received his Ph.D. degree from Monash University, Melbourne, Australia, in 2017. From 2017 to 2020, he worked as a Research Fellow at Monash University. From 2020 to 2021, he was a Postdoctoral Research Assistant with the Department of Engineering Science, University of Oxford, U.K. He is currently a Senior Lecturer in the School of Information Science at the Japan Advanced Institute of Science and Technology (JAIST). His research focuses on optical wireless communications.

October 27 · Keynote Session

Prof. Celimuge Wu

The University of Electro-Communications, Japan

Session: Keynote Session
Time: 10:30–12:00, October 27

Talk title

Semantic Communications for Remote Driving

From Data to Meaning

Abstract

The rapid growth of multimedia data and real-time intelligent applications demands more efficient and low-latency communication. Semantic communications address this challenge by transmitting meaningful information rather than raw data. This talk presents a low-latency video semantic communication framework for remote driving based on an asymmetric encoder-decoder architecture. Only essential semantic features are transmitted, while generative AI reconstructs semantically consistent video at the receiver. A prototype demonstrates its practical feasibility.

Biography

Celimuge Wu received his PhD degree from The University of Electro-Communications, Japan. He is currently a professor and the director of Meta-Networking Research Center, The University of Electro-Communications. His research interests include Semantic Communications, Vehicular Networks, Edge Computing, IoT, and AI for Wireless Networking and Computing. He serves as an associate editor of IEEE Transactions on Networking, IEEE Transactions on Cognitive Communications and Networking, IEEE Transactions on Network Science and Engineering, and IEEE Transactions on Green Communications and Networking. He is a recipient of 2021 IEEE Communications Society Outstanding Paper Award, 2021 IEEE Internet of Things Journal Best Paper Award, IEEE Computer Society 2020 Best Paper Award and IEEE Computer Society 2019 Best Paper Award Runner-Up. He is an IEEE Vehicular Technology Society Distinguished Lecturer. He is a Fellow of Asia-Pacific Artificial Intelligence Association (AAIA).