Zhenyu Yan


I am a Research Assistant Professor at The Chinese University of Hong Kong (CUHK), Department of Information Engineering. Before joining CUHK, I was a Research Fellow at School of Computer Science and Engineering, Nanyang Technological University. I received my Ph.D. from Nanyang Technological University, Singapore.

My research includes Internet-of-Things sensing, resilient AIoT systems, and cyber-physical systems.

🎓 I am looking for self-motivated Ph.D. students, Postdocs, Research Assistants in general topics of AIoT. More details can be found at here.

selected publications

  1. MobiCom ’22
    VIPS: Real-Time Perception Fusion for Infrastructure-Assisted Autonomous Driving
    Shi, Shuyao, Cui, Jiahe, Jiang, Zhehao, Yan, Zhenyu, Xing, Guoliang, Niu, Jianwei, and Ouyang, Zhenchao
    In The 28th Annual International Conference on Mobile Computing and Networking (2022) (Conditionally Accepted, Acceptance ratio: 41/314=18.2%)
  2. PhyAug: Physics-Directed Data Augmentation for Deep Sensing Model Transfer in Cyber-Physical Systems
    Luo, Wenjie, Yan, Zhenyu, Song, Qun, and Tan, Rui
    In The 20th International Conference on Information Processing in Sensor Networks (2021) (Acceptance ratio: 26/105=24.8%)
    Best Artifact Award Runner-Up
  3. Towards Touch-to-Access Device Authentication Using Induced Body Electric Potentials
    Yan, Zhenyu, Song, Qun, Tan, Rui, Li, Yang, and Kong, Adams Wai Kin
    In The 25th Annual International Conference on Mobile Computing and Networking (2019) (Acceptance ratio: 55/290=18.9%)
  4. Moving Target Defense for Embedded Deep Visual Sensing against Adversarial Examples
    Song, Qun, Yan, Zhenyu, and Tan, Rui
    In The 17th ACM Conference on Embedded Networked Sensor Systems (2019) (Acceptance ratio: 28/144=19%)
  5. Application-Layer Clock Synchronization for Wearables Using Skin Electric Potentials Induced by Powerline Radiation
    Yan, Zhenyu, Li, Yang, Tan, Rui, and Huang, Jun
    In The 15th ACM Conference on Embedded Network Sensor Systems (2017) (Acceptance ratio: 26/151=17%)