Technical Tracks

Track 9: Emerging Topics in Networking (e.g., Quantum Networking, Distributed Quantum Computing, Distributed Machine Learning)
Track Co-Chairs:

Description:
This track explores innovative research at the intersection of quantum computing, artificial intelligence, and next-generation wireless networks. As 5G progresses toward 6G and beyond, traditional methods for communication, resource management, and security are reaching their limits. Emerging quantum technologies combined with advanced machine learning approaches open new possibilities for scalable, efficient, and secure network design. We invite contributions that propose novel models, algorithms, and architectures that integrate quantum and hybrid quantum–classical methods to enhance wireless and social networks, with particular attention to resource optimization, intelligent management, and trustworthy communication.

Track Topics:
• Quantum Federated/ Meta/ Adaptive Learning for Wireless Networks
• Quantum Generative AI-enhanced Edge Computing for Resource Optimization in Wireless Networks
• Hybrid Quantum-Classical Machine Learning for Wireless/Social Network Efficiency
• Quantum-Enhanced Wireless Communications Networks. AI/ML-Driven Optimization for Multi-Agent Wireless/ Social Networks
• Quantum DRL and Quantum Neuromorphic Computing for Wireless Networks
• Quantum Approaches for Advanced Resource Management of Wireless Networks
• Energy Efficiency, Security, and Privacy in Quantum-Driven Wireless Systems
• Energy- and Delay-Sensitive Quantum-Driven Wireless/Social Networks
• Quantum Federated and Deep Reinforcement Learning for Resource Optimization & Management
• 6G-enabled Quantum Solutions for Wireless Networks
• Quantum-driven Network Slicing for Dynamic 5G/6G Wireless Networks

TPC list:
• Anal Paul, Yuan Ze University, Taiwan
• Van-Linh Nguyen, National Chung Cheng University, Taiwan
• Uman Khalid, Kyung Hee University, South Korea
• Saw Nang Paing, Kyung Hee University, South Korea
• Khan Awais, Kyung Hee University South Korea
• Sujan Rajbhandari, University of Strathclyde, UK
• Bishmita Hazarika, Memorial University, Canada
• Joongheon Kim, Korea University, Korea
• Samuel Yen-Chi Chen, Wells Fargo Bank, USA
• Caitao Zhan, Argonne National Lab, USA
• Cao Ren, KTH Royal Institute of Technology, Sweden