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Zhou Zhibin

Zhou Zhibin

Research Assistant Professor

  • V502d
  • +852 2766 5492
  • zhibin.zhou@polyu.edu.hk
  • Research Interests: Human-AI Interaction Design Methodology/Tools for AI-enhanced UX

Biography

Dr Zhibin Zhou is Research Assistant Professor in the School of Design at The Hong Kong Polytechnic University. Before joining PolyU, he was a temporary Research Faculty in the Hong Kong Center for Construction Robotics of the Hong Kong University of Science and Technology. He earned PhD from the Zhejiang University School of Computer Science and Technology. With a background in human-computer interaction and artificial intelligence (AI), his prior research endeavours to capture the interaction between humans and AI in order to gain a greater understanding of AI as an emerging technology for empowering the user experience (UX). In addition, he was also a visiting PhD candidate in the Politecnico di Milano, working on an AI-powered platform for facilitating the work of package designers. 

Education and Academic Qualifications

  • PhD, Zhejiang University School of Computer Science and Technology

Teaching Area

  • Human-AI Interaction 
  • Design Methodology/Tools for AI-enhanced UX   

Research Outputs

Zhou, Z., Zhuoshu Li, Yuyang Zhang, Lingyun Sun*, Transparent-AI Blueprint: Developing a conceptual tool to support the design of the transparent AI agents. International Journal of Human Computer Interaction[J], 2021 


Lingyun Sun, Yuyang Zhang, Zhou, Z*, inML Kit: Empowering the Prototype of ML-enhanced Products by Involving Designers in ML Lifecycle, Artificial Intelligence for Engineering Design, Analysis and Manufacturing[J], 2021 


Sun L, Li Z, Zhang Y, Liu Y, Lou S, Zhou Z*. Capturing the Trends, Applications, Issues, and Potential Strategies of Designing Transparent AI Agents[C]//Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. 2021: 1-8.  


Zhou Z, Sun L*, Zhang Y, et al. ML Lifecycle Canvas: Designing Machine Learning-Empowered UX with Material Lifecycle Thinking[J]. Human–Computer Interaction, 2020: 1-25. 


Sun, L, Zhou, Z, Wu, W, Zhang, Y, Zhang, R, & Xiang, W*. (2020). Developing a toolkit for proto- typing machine learning-empowered products: The design and evaluation of ML-Rapid. International Journal of Design, 14(2), 35-50.  


Zhou Z, Gong Q, Qi Z, et al. ML-Process Canvas: A Design Tool to Support the UX Design of Machine Learning-Empowered Products[C]// Extended Abstracts of the 2019 CHI Conference. 2019.  


(* for the corresponding author) 

Projects

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