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.
• Model-driven 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.

The best way to know me is to check the latest CV file.

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Accepting PhD students!

Please feel free to drop me an email to reach out at yuanjian.li@xjtlu.edu.cn; You can find more information about me by visiting my faculty page

• (as Primary PhD Supervisor) Postgraduate Research Scholarship (PGRS)-Funded PhD Project at XJTLU, FOSA2506034, DRL-Enabled Resource Coordination for Covertness-Aware and Energy-Efficient UAV-Aided IoT, CNY 297, 000
• (as Primary PhD Supervisor) XJTLU-XJTU-UoL Joint Doctoral Supervision Project, SFXJTU2506, Quantum Deep Reinforcement Learning-Aided Resource Coordination for Energy-Efficient 6G Networks (XJTU and UoL are abbreviations for Xi’an Jiaotong University and the University of Liverpool, respectively). Update: This position has been filled since September 2026. PhD student: Mr. Shen Liu, MSc from the University of Nottingham.
• (as Second PhD Supervisor) PGRS-Funded PhD Project at XJTLU, FOSLG250407, Adaptive Digital Twin Modelling and Optimization for V2X Networks in Large-Scale Traffic Scenarios, since 2025-07, CNY 297, 000