Zhengru Fang（方政儒）

PhD student Department of Computer Science City University of Hong Kong E-mail: zhefang4-c [AT] my [DOT] cityu [DOT] edu [DOT] hk Google Scholar, Github, and Researchgate

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 collaborative perception, V2X, age of information, and mobile edge computing. He has been serving as a Reviewer for ACM Computing Surveys, IEEE JSAC, IEEE TIV, IEEE IoTJ, IEEE TVT, IEEE VTM, etc.

Notice: I have received a report indicating that an individual is sending spam emails using my name (‘Zhengru Fang’ or ‘方政儒’). I urge you not to trust any content within these spam emails and take measures to safeguard your belongings. Please note that my official email address is zhefang4-c [AT] my [DOT] cityu [DOT] edu [DOT] hk.

News

• October 2024: (Paper) Our work “R-ACP: Real-Time Adaptive Collaborative Perception Leveraging Robust Task-Oriented Communications” was submitted to IEEE JSAC.

• August 2024: (Paper) Our work “Prioritized Information Bottleneck Theoretic Framework with Distributed Online Learning for Edge Video Analytics” was submitted to IEEE ToN. [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 IEEE Globecom. [code]

• August 2024: (Paper) Our work “Adaptive Communications in Collaborative Perception with Domain Alignment for Autonomous Driving” was accepted by IEEE Globecom.

• 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 IEEE 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” Fang
  

• Tsinghua University, Beijing, China, (2019 – 2022)
  Master of Engineering, Electronic Engineering
  Advisors: Prof. Yong Ren
  

• Huazhong University of Science and Technology, Wuhan, China, (2015 – 2019)
  Bachelor of Engineering, Electronics and Information Engineering
  

Recent Publications

1. 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 (DOI: 10.1109/TMC.2024.3449371), Aug. 2024.

2. 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.

3. 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.

4. 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.

5. 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.