Topic 1: Advanced network technologies, quantum machine learning, and semantic communications
This research explores the synergy of advanced network technologies, quantum machine learning (QML), and semantic communications to build next-generation intelligent and secure systems. We study 6G and Open RAN architectures, edge–cloud collaboration, and AI-driven resource management to enable ultra-reliable and low-latency connectivity for applications such as autonomous vehicles, UAV-assisted monitoring, and smart microgrids. Leveraging QML, we develop hybrid quantum–classical algorithms that accelerate learning, enhance cybersecurity, and optimize network performance. Meanwhile, semantic communications enable machines to exchange meaning rather than raw data, crucial for digital twins, collaborative robotics, and IoT ecosystems. Students will learn to design intelligent network architectures, implement QML models using platforms like Qiskit and PyTorch, and develop semantic encoders for efficient AI communications. This training equips them with the skills to innovate across quantum-intelligent networking, AI-native communications, and cyber-physical infrastructure security in smart cities and sustainable systems. In short, this project encourages the talents who are interested in the following topics:
(1) 6G networks: ISAC, wireless sensing, non-camera monitoring.
(2) Quantum machine learning: Quantum AI, quantum networks, quantum computing.
(3) Wireless and Semantic Communications: Digital twins, VR/XR