Special Session 8

AI and large language models for autonomous network management and operations

This special session is organised and supported by  the following educational partner

University of Anbar

Session Chair:

• Dr Salah A. Salman, University of Anbar, Iraq.
• Dr Ahmed J. Aljaaf, University of Anbar, Iraq.

Session Co-Chairs:

• Dr Ayad Turky, University of Sharjah, UAE.

• Dr Mohammed Ibrahim Salman, University of Anbar, Iraq.

Synopsis:

Modern communication networks have grown too complex and too dynamic for conventional manual management. This session brings together researchers and practitioners working at the frontier of AI-driven network operations — from classical machine learning and reinforcement learning to the emerging application of large language models (LLMs) in network control and troubleshooting. Together, we explore how these technologies are enabling a new generation of self-configuring, self-healing, and self-optimizing network infrastructures, and what it will take to realise truly autonomous networks at scale.

Topics:

We welcome original contributions on, but not limited to, the following themes:

• Machine learning for traffic prediction and network anomaly detection
• Self-healing and self-optimizing network architectures
• Intent-based and intent-driven networking
• Large language models for network configuration and troubleshooting
• LLM-assisted log analysis and root-cause diagnosis
• Natural-language interfaces for network control — NetGPT and NetOps copilots
• Reinforcement learning for adaptive routing and resource allocation
• AI-driven orchestration in 5G/6G and data centre networks
• Benchmarks, datasets, and evaluation frameworks for AI-powered network operations
• Trust, explainability, and safety of AI and LLM agents in production networks

 Paper Submission