Zhengru Fang（方政儒）
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PhD student |
About
Zhengru Fang received his B.S. degree (Hons.) in electronics and information engineering from the Huazhong University of Science and Technology (HUST), Wuhan, China, in 2019 and received his M.S. degree (Hons.) from Tsinghua University, Beijing, China, in 2022 (Advisors: Prof. Yong Ren). Currently, he is pursuing his PhD degree in the Department of Computer Science at City University of Hong Kong (Advisors: Prof. Yuguang “Michael” Fang). His research interests include LLM agents, tool-augmented search, multimodal model evaluation, collaborative perception, and mobile edge computing. His research work has been published in IEEE/CVF CVPR, IEEE ICRA, IEEE/ACM ToN, IEEE JSAC, IEEE TMC, and ACM MM, etc.
Contact: Currently on the job market starting in fall 2026.
News
April 2025 (Paper) Our work “AgentsCoMerge: Large Language Model Empowered Collaborative Decision Making for Ramp Merging” was accepted by IEEE TMC.
February 2025 (Paper) Our work “DeCoder Gradient Shield: Provable and High-Fidelity Prevention of Gradient-Based Box-Free Watermark Removal” was accepted by CVPR 2025. [Code]
January 2025 (Paper) Our work “Direct-CP: Directed Collaborative Perception for Connected and Autonomous Vehicles via Proactive Attention” was accepted by ICRA 2025.
December 2024: (Paper) Our work “Prioritized Information Bottleneck Theoretic Framework with Distributed Online Learning for Edge Video Analytics” was accepted by IEEE/ACM ToN. [Code]
October 2024: (Paper) Our work “R-ACP: Real-Time Adaptive Collaborative Perception Leveraging Robust Task-Oriented Communications” was submitted to IEEE JSAC. [Code]
August 2024: (Paper) Our work “PACP: Priority-Aware Collaborative Perception for Connected and Autonomous Vehicles” was accepted by IEEE TMC.
August 2024: (Paper) Our work “PIB: Prioritized Information Bottleneck Framework for Collaborative Edge Video Analytics” was accepted by Globecom 2024. [Code]
August 2024: (Paper) Our work “Adaptive Communications in Collaborative Perception with Domain Alignment for Autonomous Driving” was accepted by Globecom 2024.
April 2024: (Paper) Our work “AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learning” was submitted to IEEE TITS.
January 2024: (Paper) Our work “SmartCooper: Vehicle Collaborative Perception under Adaptive Fusion and Judger Mechanism” was accepted by ICRA 2024.
November 2023: (Paper) Our work “Towards Full-scene Domain Generalization in Multi-agent Collaborative Bird's Eye View Segmentation for Connected and Autonomous Driving” was submitted to IEEE TITS. [Code]
March 2023: (Award) Thanks to Prof. Fang's strong support, I obtained the Hong Kong PhD Fellowship Scheme (HKPFS).
March 2023: (Award) My master's thesis about IoT-based information collection system received the Excellent Master Thesis Award from the Chinese Institute of Electronics (Only 25 awardees nationwide).
Background
City University of Hong Kong, Hong Kong (2023 - now)
PhD student, Computer Science
Advisors: Prof. Yuguang “Michael” FangTsinghua University, Beijing, China, (2019 – 2022)
Master of Engineering, Electronic Engineering
Advisors: Prof. Yong RenHuazhong University of Science and Technology, Wuhan, China, (2015 – 2019)
Bachelor of Engineering, Electronics and Information Engineering
Recent Publications
Z. Fang, S. Hu, Z. Chang, Y. Guo, Y. Tao, H. Liu, M. Ruan, J. Huang, Y. Fang, “Budget Control for Tool-Augmented LLM Search Agents”, 2026 (Under Review). [PDF]
Z. Fang, Y. Guo, F. Liu, Y. Zhang, Y. Tao, S. Hu, W. Ding, Y. Fang, “Agent-Centric Visual Reinforcement Learning under Dynamic Perturbations”, 2026 (Under Review). [PDF] [Code]
Z. Fang, Y. Guo, Y. Ma, S. Hu, X. Zhang, H. Cao, W. Ding, Y. Fang, “CXR-ContraBench: Benchmarking Negated-Option Attraction in Medical VLMs”, 2026 (Under Review). [PDF] [Code]
Z. Fang, S. Hu, J. Wang, Y. Deng, X. Chen, Y. Fang, “Prioritized Information Bottleneck Theoretic Framework with Distributed Online Learning for Edge Video Analytics”, IEEE/ACM Transactions on Networking, Dec. 2024 (Accepted). [PDF] [Code]
Z. Fang, S. Hu, H. An, Y. Zhang, J. Wang, H. Cao, X. Chen, Y. Fang, “PACP: Priority-Aware Collaborative Perception for Connected and Autonomous Vehicles”, IEEE Transactions on Mobile Computing, vol. 23, no. 12, pp. 15003-15018, Dec. 2024. [PDF] [Code]
Z. Fang, J. Wang, Y. Ren, Z. Han, H. V. Poor and L. Hanzo, “Age of Information in Energy Harvesting Aided Massive Multiple Access Networks”, IEEE Journal on Selected Areas in Communications, vol. 40, no. 5, pp. 1441-1456, May 2022. [PDF] [Code]
Z. Fang, J. Wang, J. Du, X. Hou, Y. Ren and Z. Han, “Stochastic Optimization-Aided Energy-Efficient Information Collection in Internet of Underwater Things Networks”, IEEE Internet of Things Journal, vol. 9, no. 3, pp. 1775-1789, Feb. 2022. [PDF] [Code]
Z. Fang, J. Wang, C. Jiang, Q. Zhang and Y. Ren, “AoI-Inspired Collaborative Information Collection for AUV-Assisted Internet of Underwater Things”, IEEE Internet of Things Journal, vol. 8, no. 19, pp. 14559-14571, Oct. 2021. [PDF] [Code]
Z. Fang, J. Wang, C. Jiang, X. Wang and Y. Ren, “Average Peak Age of Information in Underwater Information Collection with Sleep-scheduling”, IEEE Transactions on Vehicular Technology, vol. 71, no. 9, pp. 10132-10136, Sep. 2022. [PDF] [Code]