Bio

Dr. Qihua Zhou is an Assistant Professor (“Hundred Talents Program”) with the College of Computer Science and Software Engineering at Shenzhen University. He is a co-founder of Hong Kong DrBody Corporation Limited.

He received his Ph.D. degree in the Department of Computing, Hong Kong Polytechnic University, advised by Prof. Song Guo. Before that, he received a Ph.D. degree in the College of Automation and College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, advised by Prof. Yanfei Sun.

He has long been engaged in the research fields of Edge AI, Tiny Machine Learning, Video Streaming Systems, and Distributed Machine Learning. He has published multiple top-tier international journal and conference papers, including IEEE TPAMI, IEEE TPDS, IEEE TC, IEEE TMC, USENIX ATC, NeurIPS, AAAI, IJCAI, IEEE ICDCS, IEEE IPDPS, etc.

He serves as a reviewer for multiple important international conferences (NeurIPS, ICLR, ICML, AAAI, ICCV, CVPR, ECCV, IJCAI, INFOCOM, etc) and journals (IEEE TMC, IEEE IoTJ, ACM CSUR, IEEE TIT, etc).

 

Education

  • The Hong Kong Polytechnic University, Hong Kong, 2019 – 2023
    Ph.D. @ Department of Computing, Pervasive Intelligence Lab
    Supervisor: Prof. Song Guo

  • Nanjing University of Posts and Telecommunications, China, 2015 – 2019
    Ph.D. @ College of Automation and College of Artificial Intelligence
    Supervisor: Prof. Yanfei Sun

  • Nanjing University of Posts and Telecommunications, China, 2011 – 2015
    B.Eng. @ Department of Computer Science
    Major: Information Security

 

Awards

  • Spotlight on Transactions, 2021
    First Author, “A Comprehensive Inspection of the Straggler Problem”, IEEE Transactions on Computers
  • NVIDIA Hackthon Award, 2021
    Team Leader, “On-device Human Pose Tracking System with NVIDIA TensorRT”
  • Second prize of China Medical Device Innovation Competition (中国医疗器械创新创业大赛二等奖), 2021
    Collaborator, “Dr. Body无辐射不良体态检测及管理系统”

 

Services

Conference Program Committee:

  • AAAI Conference on Artificial Intelligence (AAAI) [2025]

Conference Reviewer:

  • Annual Conference on Neural Information Processing Systems (NeurIPS) [2022, 2023, 2024]
  • International Conference on Learning Representations (ICLR) [2023, 2024]
  • International Conference on Machine Learning (ICML) [2022, 2023, 2024]
  • AAAI Conference on Artificial Intelligence (AAAI) [2023, 2024]
  • International Conference on Computer Vision (ICCV) [2023]
  • IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR) [2022, 2023, 2024]
  • European Conference on Computer Vision (ECCV) [2022, 2024]
  • IEEE International Conference on Computer Communications (INFOCOM) [2022, 2023, 2024]
  • International Joint Conference on Artificial Intelligence (IJCAI) [2024]
  • IEEE International Conference on Pervasive Computing and Communications (PerCom) [2022]

Journal Reviewer:

  • IEEE Transactions on Parallel and Distributed Systems (TPDS) [2024]
  • IEEE Transactions on Mobile Computing (TMC) [2023, 2024]
  • IEEE Internet of Things Journal (IoTJ) [2022, 2023, 2024]
  • ACM Computing Surveys (CSUR) [2024]
  • IEEE Transactions on Information Theory (TIT) [2024]
  • Journal of Parallel and Distributed Computing (JPDC) [2022]

 

Teaching

I have served as a teaching assistant at PolyU and HKUST in the following courses.

  • COMP6311: Advanced Data Analytics (Fall 2023)
    Ph.D. Course, The Hong Kong University of Science and Technology
  • COMP5434: Big Data Computing (Spring 2023)
    M.Sc. Course, The Hong Kong Polytechnic University
  • COMP5511: Artificial Intelligence Concepts (Fall 2022)
    M.Sc. Course, The Hong Kong Polytechnic University
  • COMP5523: Computer Vision and Image Processing (Spring 2022)
    M.Sc. Course, The Hong Kong Polytechnic University
  • COMP6706: Advanced Topics in Visual Computing (Fall 2021)
    Ph.D. Course, The Hong Kong Polytechnic University
  • COMP6434: Big Data Analytics and Artificial Intelligence (Spring 2021)
    Ph.D. Course, The Hong Kong Polytechnic University
  • COMP2011: Data Structures (Fall 2020)
    Undergraduate Course, The Hong Kong Polytechnic University
  • COMP1001: Computational Thinking and Problem Solving (Fall 2019)
    Undergraduate Course, The Hong Kong Polytechnic University

 

Monograph

  • Song Guo, Qihua Zhou, “Machine Learning on Commodity Tiny Devices: Theory and Practice”, Taylor & Francis Books, Routledge, CRC Press, 2022.

 

Patents

  • Song Guo, Qihua Zhou, and Yufeng Zhan, “Distributed deep learning method, device, parameter server and working node” (分布式深度学习方法、装置、参数服务器及工作节点), China Patent, No. 201911352575.9.
  • Song Guo, Qihua Zhou, and Xin Xie, “A method and system for training models based on data quantization and hardware acceleration” (一种训练基于数据量化与硬件加速的模型的方法及系统), China Patent, No. 202110211440.1.

 

Internship

  • Microsoft Research Asia, Shanghai, 2022
    Research Intern @ AI system group
    Mentor: Dr. Zhenhua Han