Call for Papers
The topics of interest for submission include, but are not limited to:
Track I: Machine Learning Theories and Methods
• Supervised learning, unsupervised learning, self-supervised learning, and reinforcement learning
• Deep learning and novel neural network architectures
• Transfer learning and domain adaptation
• Federated learning and distributed learning
• Graph neural networks and representation learning
• Generative artificial intelligence
• Explainable machine learning
• Few-shot and zero-shot learning
• Multimodal learning and cross-modal understanding
Track II: Intelligent Communication and Networking Technologies
• 5G/6G communication systems and networks
• Semantic communication and information theory
• Communication signal processing and channel coding
• Massive MIMO and reconfigurable intelligent surfaces
• Millimeter-wave and terahertz communications
• Visible light communication and quantum communication
• Non-terrestrial networks and satellite communications
• Vehicle-to-everything (V2X) communication technologies
• UAV communication and networking
Track III: Machine Learning-Driven Communication System Optimization
• AI-driven communication and network operations and control
• Applications of deep learning and reinforcement learning in communications
• Intelligent scheduling of wireless network resources and spectrum management
• Edge computing and communication convergence
• Network traffic prediction and anomaly detection
• Intelligent optimization algorithms in communication systems
• Digital twin-driven communication network optimization
• Autonomous networks and automated operations for communication systems
Track IV: Integrated Sensing, Communication, and Computing and Frontier Applications
• Integrated sensing and communication (ISAC) systems
• Intelligent Internet of Things and industrial Internet communications
• Generative AI-empowered communication system design
• AI-driven semantic communication and content distribution
• Intelligent reflecting surface-assisted communications
• Federated learning and privacy protection in communication systems
• Machine learning in network security and information privacy
• Cognitive radio and intelligent spectrum sharing