Dr K.F. Chu

Dr Kai-Fung Chu

Marie Skłodowska-Curie Fellow

Department of Engineering, University of Cambridge

Dr Kai-Fung Chu is a Marie Skłodowska-Curie Fellow in the Department of Engineering, University of Cambridge. He received the Ph.D. degree in Electrical and Electronic Engineering from The University of Hong Kong, and the M.Sc. (Distinction) and B.Eng. (First Class Honors) degrees in Electronic and Information Engineering from The Hong Kong Polytechnic University. Prior to joining the University of Cambridge, he was a Research Assistant Professor at the Department of Computing, The Hong Kong Polytechnic University, and a Research Fellow of the School of Aerospace, Transport and Manufacturing, Cranfield University. He also worked in the industry as an engineer for several years. His research interests include multi-agent systems, mobile robots, autonomous vehicles, and intelligent transportation systems.

Jounrals

1. Yang Chen*, Saba Al-Rubaye, Antonios Tsourdos, Kai-Fung Chu, Zhuangkun Wei, Lawrence Baker, and Colin Gillingham, “Federated Deep Reinforcement Learning based Intelligent Surface Configuration in 6G Secure Airport Networks,” IEEE Transactions on Intelligent Transportation Systems.
2. Chenchen Fan, Kai-Fung Chu*, Xiaomei Wang, Ka-Wai Kwok, and Fumiya Iida, “State Transition Learning with Limited Data for Safe Control of Switched Nonlinear Systems,” Neural Networks, doi: 10.1016/j.neunet.2024.106695.
3. Kai-Fung Chu*, Haiyue Yuan, Jinsheng Yuan, Weisi Guo, Nazmiye Ozkan, and Shujun Li, “A Survey of AI-Related Cyber Security Risks and Countermeasures in Mobility-as-a-Service”, IEEE Intelligent Transportation Systems Magazine, doi: 10.1109/MITS.2024.3427655.
4. Mengbang Zou, Weisi Guo*, and Kai-Fung Chu, “Rewiring Complex Networks to Achieve Cluster Synchronization using Graph Convolution Networks with Reinforcement Learning,” IEEE Transactions on Network Science and Engineering, doi: 10.1109/TNSE.2024.3410694.
5. Kai-Fung Chu* and Weisi Guo, “Multi-agent Reinforcement Learning-based Passenger Spoofing Attack on Mobility-as-a-Service,” IEEE Transactions on Dependable and Secure Computing, doi: 10.1109/TDSC.2024.3379283.
6. Kai-Fung Chu* and Weisi Guo, “Privacy-Preserving Federated Deep Reinforcement Learning for Mobility-as-a-Service,” IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2023.3317358.
7. Chenchen Fan, James Lam*, Kai-Fung Chu, Xiujuan Lu, and Ka-Wai Kwok*, “Output Reachable Set-based Leader-following Consensus of Positive Agents over Switching Networks,” IEEE Transactions on Cybernetics, doi: 10.1109/TCYB.2023.3286416
8. Kai-Fung Chu* and Weisi Guo, “Deep Reinforcement Learning of Passenger Behavior in Multimodal Journey Planning with Proportional Fairness,” Neural Computing and Applications, vol. 35, pp. 20221-20240, September 2023, doi: 10.1007/s00521-023-08733-4.
9. Kai-Fung Chu, Albert Y.S. Lam*, Ka Ho Tsoi, Zhiran Huang, and Becky P.Y. Loo, “Deep Residual Learning for Estimated Time of Arrival,” IEEE Access, vol. 11, pp. 76095– 76107, July 2023, doi: 10.1109/ACCESS.2023.3294345.
10. Kai-Fung Chu*, Albert Y.S. Lam, and Victor O.K. Li, “Traffic Signal Control Using End-to-End Off-policy Deep Reinforcement Learning,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 7, pp. 7184-7195, July 2022, doi: 10.1109/TITS.2021.3067057.
11. Kai-Fung Chu*, Albert Y.S. Lam, and Victor O.K. Li, “Joint Rebalancing and Vehicle-to-Grid Coordination for Autonomous Vehicle Public Transportation System,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 7, pp. 7156-7169, July 2022, doi: 10.1109/TITS.2021.3067044.
12. Kai-Fung Chu, Albert Y.S. Lam*, Chenchen Fan, and Victor O.K. Li, “Disturbance-Aware Neuro-Optimal System Control Using Generative Adversarial Control Networks,” IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 10, pp. 4565-4576, Oct. 2021, doi: 10.1109/TNNLS.2020.3022950.
13. Kai-Fung Chu*, Albert Y.S. Lam, and Victor O.K. Li, “Deep Multi-Scale Convolutional LSTM Network for Travel Demand and Origin-Destination Predictions,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 8, pp. 3219-3232, August 2020, doi: 10.1109/TITS.2019.2924971.
14. Kai-Fung Chu*, Albert Y.S. Lam, and Victor O.K. Li, “Dynamic Lane Reversal Routing and Scheduling for Connected Autonomous Vehicles: Formulation and Distributed Algorithm,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 6, pp. 2557-2570, June 2020, doi: 10.1109/TITS.2019.2920674.