Shuai Ma (马帅)

Hey, this is Shuai. I am a PhD candidate in HCI Lab at Hong Kong University of Science and Technology (HKUST). I'm fortunate to be advised by Prof. Xiaojuan Ma.

My research interest focuses on improving human‑AI collaboration (objectively and subjectively) with human‑centered design. My previous work leverages user research methods, builds upon theories from cognitive science and social science, targets personalization, transparency, and trust calibration issues when humans interact with AI agents/systems.

  • In the method part, I have developed computational models to model users (e.g., their preferences, and capabilities) allowing the AI system to adapt to individual users to boost task performance and user experience. I also designed effective and transparent communication mechanisms between humans and the black‑box AI. The proposed approaches have been verified in 1) promoting humans' appropriate reliance on AI's recommendations in AI‑assisted decision‑making and 2) shaping humans' mental models in machine/robot teaching.

  • In the application part, I leveraged theories from cognitive science and social science, and adopted a human‑centered design to develop AI‑empowered systems to assist users in solving real‑world problems in various domains, including Education & Learning (e.g., self‑paced programming learning, online classes teaching, MOOC learning), Work & Creation (e.g., phototaking, video‑editing), Healthcare & Wellbeing (e.g., online health community support, Parkinson's disease detection).

a portrait of shuai ma

Selected Publications (Full publications can be viewed through Google Scholar)

Who Should I Trust: AI or Myself? Leveraging Human and AI Correctness Likelihood to Promote Appropriate Trust in AI-Assisted Decision-Making

Shuai Ma, Ying Lei, Xinru Wang, Chengbo Zheng, Chuhan Shi, Ming Yin, Xiaojuan Ma. (CHI 2023)
[PDF] [Code] [Live Demo] [Video]

We proposed to promote humans' appropriate trust based on the correctness likelihood of both sides at a task-instance level. Results from a between-subjects experiment (N=293) showed that our CL exploitation strategies promoted more appropriate human trust in AI, compared with only using AI confidence.

RetroLens: A Human-AI Collaborative System for Multi-step Retrosynthetic Route Planning

Chuhan Shi, Yicheng Hu, Shenan Wang, Shuai Ma, Chengbo Zheng, Xiaojuan Ma, Qiong Luo. (CHI 2023)

Targeting Multi-step Human-AI Collaboration task for chemists, we proposed a human-AI collaborative system, RetroLens, through a participatory design process. AI can contribute by two approaches: joint action and algorithm-inthe-loop.

Competent but Rigid: Identifying the Gap in Empowering AI to Participate Equally in Group Decision-Making

Chengbo Zheng, Yuheng Wu, Chuhan Shi, Shuai Ma, Jiehui Luo, Xiaojuan Ma. (CHI 2023)

What will happen if AI participate equally in human group decision-making? We find that although the voice of AI is considered valuable, AI still plays a secondary role in the group because it cannot fully follow the dynamics of the discussion and make progressive contributions. Moreover, the divergent opinions of our participants regarding an "equal AI" shed light on the possible future of human-AI relations.

Modeling Adaptive Expression of Robot Learning Engagement and Exploring its Effects on Human Teachers

Shuai Ma, Mingfei Sun, Xiaojuan Ma. (TOCHI 2022)
[PDF] [Code] [Live Demo] [Video]

For human-robot teaching scenario, we propose an adaptive modeling and expression method to facilitate the transparent communication of robots' learning statuses during human demonstration.

Glancee: An Adaptable System for Instructors to Grasp Student Learning Status in Synchronous Online Classes

Shuai Ma, Taichang Zhou, Fei Nie, Xiaojuan Ma. (CHI 2022)
[PDF] [Code] [Live Demo] [Video]

Focusing on synchronous online classes (e.g., real-time Zoom-based classes), Glancee address instructors’ difficulty to observe students’ learning status due to students’ unwillingness to show their videos. Specifically, we mitigate the gap that lack of empirical investigation on instructors’ preferences and lack of exploration of designing adaptable systems to meet the needs of individual instructors.

Latest News

  • 2023-11-9 | Arrived in Zurich. Visiting ETH.
  • 2023-4-24 | Reconnect at CHI! Hamburg.
  • 2023-1-24 | Happy to be a student volunteer at CHI 2023! See U in Germany.
  • 2023-1-20 | Start my AC work for CHI 2023 LBW.
  • 2023-1-14 | Three papers got accepted by CHI 2023! Congrats to my co-authors.
  • 2022-8-5 | Our paper 'Modeling Adaptive Expression of Robot Learning Engagement' has been accepted by TOCHI!
  • 2022-4-19 | I passed my PhD Qualifying Exam and became a PhD candidate! Thanks for my committee members' valuable feedback!
  • 2022-3-10 | Happy to be a student volunteer at CHI 2022!
  • 2022-2-10 | Our paper Glancee is conditionally accepted at CHI 2022.
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  • 2021-2022 Fall COMP 1021 - Introduction to Computer Science (TA, @HKUST)
  • 2020-2021 Spring COMP 1021 - Introduction to Computer Science (TA, @HKUST)
  • 2018-2019 Introduction to Natural User Interfaces (Lecturer, @Beijing Zhongguancun No.1 Primary School)
  • 2018 Introduction to Natural User Interfaces (Lecturer, @Beijing Science and Innovation Open Day)


Program Committee: ACM CHI '23 LBW
Conference Review: ACM CHI '24 (1), '23 (2), '22, '20, '19, CSCW '23, UIST '22, CHI EA '23, '22, WWW '21
Journal Review: ACM TOCHI, ACM TiiS, CCF TOPCI
Volunteer: CHI' 23 (3), CHI' 22 (4)
(1) (2) received Special Recognition for Outstanding Reviews for CHI 2023, CHI 2024
(3) (4) received Student Volunteer Award for CHI 2022, CHI 2023


  • 2023 HKUST PhD Overseas Research Award
  • 2020 HKUST Redbird PhD Scholarship
  • 2019 CHI Honorable Mention Award (first author)
  • 2019 President Scholarship in Chinese Academy of Sciences (in Chinese, 中科院院长奖学金, 1% selected)
  • 2018 National Scholarship for Graduate (in Chinese, 研究生国家奖学金, 1% selected)
  • 2018 Winner of Huawei Cup Free Software Programming Competition (Ranked 1st among 50+ teams)
  • 2017 Excellence Award for Science Creation Program of Chinese Academy of Sciences
  • 2017 Special Scholarship for Undergraduates (in Chinese, 本科生特奖, 0.1% selected)
  • 2016 National Scholarship for Undergraduate (in Chinese, 本科生国家奖学金, 1% selected)
  • 2018 Pacemaker of Merit Student of UCAS (1% selected)
  • 2017 Excellent Graduates in Harbin Institute of Technology
  • 2016 Pacemaker of Merit Student of HIT (0.1% selected)
  • 2016 Pacemaker to Merit Student Cadres of HIT (0.1% selected)
  • 2016 Winner of The 5th National Marine Vehicle Design and Manufacturing Competition (Ranked 3rd among 100+ teams)
  • 2016 Winner of The 18th National Robot Championship (Ranked Top 5 among 100+ teams)
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