My interdisciplinary research focuses on AI for Next-Generation Wireless Systems.

Two zoomed-in examples are

• Deep Reinforcement Learning (DRL)-enabled joint computation and communication resource coordination for many-UAV many-user multi-access edge computing (MEC) in the Internet of Things (IoT) scenarios.
• Machine learning (ML)-aided sparsity-aware channel estimation and efficient receiver design for Terahertz (THz) ultra-massive multiple-input multiple-output (UM-MIMO) transmissions, where near-field communication characteristics are highlighted.

Broadly speaking, my research expertise and interests include

1. THz UM-MIMO Transmissions
2. Near-Field Communications
3. DRL-Driven Joint Communication and Computation Resource Management
4. Space-Air-Ground Integrated Networks
5. Quantum Machine Learning (QML) for Next-Generation Wireless Systems
6. Secure and Covert Communications

I have authored over 20 papers in the interdisciplinary research direction of wireless communications and signal processing, machine learning, and quantum computing, in top-tier journals and prestigious conferences including IEEE TWC, IEEE TCOM, IEEE WCL, IEEE GLOBECOM, and IEEE ICC. I am also an active reviewer for these journals, conferences and beyond. I have authored 9 CN patents in the fields of wireless communications and signal processing. I served as a session chair for IEEE ICC 2022: Selected Areas in Communications: Machine Learning for Communications Track - Networks.

The best way to know me is to check the latest CV file. Besides, copies of my PhD and MEng theses are accessible in PhD Thesis and MEng Thesis, respectively.