Workshop IV


AI-Driven Edge Intelligence for 6G and Beyond

Workshop Organising Committee

Chair

Yan Zhang

University of Electronic Science and Technology of China, China

yanzhang@ieee.org

Chair

Min Zhang

University of Waikato, New Zealand

min.zhang@waikato.ac.nz

TPC Program Chair

Yueyue Dai

Huazhong University of Science and Technology, China

yueyuedai@hust.edu.cn

TPC Program Chair

Yiwen Wu

Southwest Minzu University, China

yiwenwu@ieee.org

Abstract

With the rapid development of 6G and beyond networks, edge intelligence is becoming a key enabler for future wireless systems, the Internet of Things (IoT), and distributed intelligent applications. Different from conventional AI-assisted optimisation, AI-driven edge intelligence deeply integrates learning, reasoning, prediction, and adaptation into network architecture, resource management, service provisioning, and autonomous decision-making. However, future edge networks will involve massive heterogeneous devices, dynamic wireless environments, distributed resources, and diverse service requirements, posing new challenges for the joint orchestration of communication, computing, caching, sensing, and energy resources. This workshop aims to bring together researchers and practitioners from academia and industry to explore recent advances and future directions in AI-driven edge intelligence, including digital twin edge networks, federated learning, agentic AI, foundation models, semantic communications, trustworthy AI, and intelligent resource orchestration for 6G and beyond networks.

Potential Topics

  • —  AI-driven architectures for 6G edge networks
  • —  Edge intelligence for future wireless systems
  • —  Communication, computing, caching, and sensing orchestration
  • —  Resource allocation and service provisioning at the edge
  • —  Task offloading and edge service placement
  • —  Distributed and federated learning for edge networks
  • —  Reinforcement learning for dynamic network optimisation
  • —  Multi-agent collaboration in edge intelligence systems
  • —  Agentic AI for autonomous network management
  • —  Foundation models for wireless and edge intelligence
  • —  Digital twin edge networks and network automation
  • —  Semantic communications and task-oriented networking
  • —  Trustworthy and privacy-preserving edge intelligence
  • —  Blockchain-assisted trust and distributed coordination
  • —  Energy-efficient and low-latency edge services
  • —  Intelligent applications in Industrial IoT, vehicular networks, UAV networks, and smart cities
  • —  Testbeds, prototypes, and real-world deployments

Submission

Submission details refer to the ICAIT 2026 website: https://www.icait.org/submission.html