A Deep Reinforcement Learning based Resource Allocation Method for Urban Rail Transit Cloud Systems. - Ziheng Li; Li Zhu 002; Yang Li 118; Hao Liang 005; Hao Wang (ITSC, 2021)

A Potential Game Based Offloading Scheme for Edge Computing-Enabled Automatic Train Operation Systems. - Siyu Wei; Li Zhu 002; Yang Li 118; Hao Liang 005 (ITSC, 2021)

Joint Security and Train Control Design in Blockchain-Empowered CBTC System. - Li Zhu 002; Hao Liang 005; Hongwei Wang 008; Bin Ning; Tao Tang 004 (IEEE Internet Things J., 2022)

When Blockchain Meets Urban Rail Transit: Current Prospects, Case Studies, and Future Challenges. - Hao Liang 005; Li Zhu 002; F. Richard Yu (IEEE Intell. Transp. Syst. Mag., 2023)

A Cross-Layer Defense Method for Blockchain Empowered CBTC Systems Against Data Tampering Attacks. - Hao Liang 005; Li Zhu 002; F. Richard Yu; Xuan Wang (IEEE Trans. Intell. Transp. Syst., 2023)

A Learning Based Intelligent Train Regulation Method With Dynamic Prediction for the Metro Passenger Flow. - Li Zhu 002; Chunzi Shen; Xi Wang 020; Hao Liang 005; Hongwei Wang 008; Tao Tang 004 (IEEE Trans. Intell. Transp. Syst., 2023)

Collaborative Edge Intelligence Service Provision in Blockchain Empowered Urban Rail Transit Systems. - Hao Liang 005; Li Zhu 002; F. Richard Yu (IEEE Internet Things J., 2024)

Blockchain-Empowered Edge Intelligence for TACS Obstacle Detection: System Design and Performance Optimization. - Hao Liang 005; Li Zhu 002; F. Richard Yu; Zhaowei Ma (IEEE Trans. Ind. Informatics, 2024)

Cloud-Edge-End Collaboration for Intelligent Train Regulation Optimization in TACS. - Hao Liang 005; Li Zhu 002; F. Richard Yu; Chau Yuen (IEEE Trans. Veh. Technol., 2025)