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Huamin Qu

Also published under: H. Qu

Publications
172
Citations
5,060
Publications by Year
20052025
Co-Authors:
Show All Co-Authors (372)
Image of author Huamin Qu

Huamin Qu

Also published under: H. Qu

Affiliation

Hong Kong University of Science and Technology, Hong Kong

Publication Topics

Biography

Huamin Qu (M'07) received the B.S. degree in mathematics from the Xi'an Jiaotong University, Xi'an, China, and the M.S. and Ph.D. degrees in computer science from the Stony Brook University, Stony Brook, NY, USA, in 2004.,He is an Associate Professor with the Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong. He has coauthored more than 60 refereed papers, including 20 papers in the IEEE Transactions on Visualization and Computer Graphics (TVCG). His main research interests are in visualization and computer graphics.,Prof. Qu serves on the steering committee of the IEEE Pacific Visualization Conferences and is an Associate Editor of IEEE TVCG. He received the Honorable Mentio...
Publications
172
Citations
5,060
Publications by Year
20052025
Co-Authors:
Show All Co-Authors (372)
Author's Published Works

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Motivating Students with Different Needs to Learn Chinese in a Mixed-Background Classroom by Robot-Assisted Learning

Ka-Yan Fung;Kwong-Chiu Fung;Tze Leung Rick Lui;Kuen-Fung Sin;Lik-Hang Lee;Huamin Qu;Shenghui Song

IEEE Transactions on Learning Technologies
Year: 2025 | Early Access Article |
Mastering the visually complex characters of the Chinese language poses significant challenges for students. The situation is even worse in Hong Kong, where students with different backgrounds, including students with/without dyslexia and non-Chinese speaking students (NCS), are placed in the same class. Interactive design has been proven effective in enhancing students' learning performance and e...Show More

Motivating Students with Different Needs to Learn Chinese in a Mixed-Background Classroom by Robot-Assisted Learning

Ka-Yan Fung;Kwong-Chiu Fung;Tze Leung Rick Lui;Kuen-Fung Sin;Lik-Hang Lee;Huamin Qu;Shenghui Song

Year: 2025 | Early Access Article |

Personalized Dual-Level Color Grading for 360-degree Images in Virtual Reality

Lin-Ping Yuan;John J. Dudley;Per Ola Kristensson;Huamin Qu

IEEE Transactions on Visualization and Computer Graphics
Year: 2025 | Early Access Article |
The rising popularity of 360-degree images and virtual reality (VR) has spurred a growing interest among creators in producing visually appealing content through effective color grading processes. Although existing computational approaches have simplified the global color adjustment for entire images with Preferential Bayesian Optimization (PBO), they neglect local colors for points of interest an...Show More

Personalized Dual-Level Color Grading for 360-degree Images in Virtual Reality

Lin-Ping Yuan;John J. Dudley;Per Ola Kristensson;Huamin Qu

Year: 2025 | Early Access Article |

Illuminating the Scene: How Virtual Environments and Learning Modes Shape Film Lighting Mastery in Virtual Reality

Zheng Wei;Jia Sun;Junxiang Liao;Lik-Hang Lee;Chan In Sio;Pan Hui;Huamin Qu;Wai Tong;Xian Xu

IEEE Transactions on Visualization and Computer Graphics
Year: 2025 | Early Access Article |
In virtual reality (VR) education, particularly in creative fields like film production, the role of different virtual environments in shaping learning outcomes remains underexplored. This study investigates how three distinct environments—baseline, a dynamic beach setting, and a familiar office space—affect students' ability to learn film lighting techniques and whether team-based learning offers...Show More

Illuminating the Scene: How Virtual Environments and Learning Modes Shape Film Lighting Mastery in Virtual Reality

Zheng Wei;Jia Sun;Junxiang Liao;Lik-Hang Lee;Chan In Sio;Pan Hui;Huamin Qu;Wai Tong;Xian Xu

Year: 2025 | Early Access Article |

Exploring Spatial Hybrid User Interface for Visual Sensemaking

Wai Tong;Haobo Li;Meng Xia;Wong Kam-Kwai;Ting-Chuen Pong;Huamin Qu;Yalong Yang

IEEE Transactions on Visualization and Computer Graphics
Year: 2025 | Early Access Article |
We built a spatial hybrid system that combines a personal computer (PC) and virtual reality (VR) for visual sensemaking, addressing limitations in both environments. Although VR offers immense potential for interactive data visualization (e.g., large display space and spatial navigation), it can also present challenges such as imprecise interactions and user fatigue. At the same time, a PC offers ...Show More

Exploring Spatial Hybrid User Interface for Visual Sensemaking

Wai Tong;Haobo Li;Meng Xia;Wong Kam-Kwai;Ting-Chuen Pong;Huamin Qu;Yalong Yang

Year: 2025 | Early Access Article |

Narrative Player: Reviving Data Narratives with Visuals

Zekai Shao;Leixian Shen;Haotian Li;Yi Shan;Huamin Qu;Yun Wang;Siming Chen

IEEE Transactions on Visualization and Computer Graphics
Year: 2025 | Early Access Article |
Data-rich documents are commonly found across various fields such as business, finance, and science. However, a general limitation of these documents for reading is their reliance on text to convey data and facts. Visual representation of text aids in providing a satisfactory reading experience in comprehension and engagement. However, existing work emphasizes presenting the insights within phrase...Show More

Narrative Player: Reviving Data Narratives with Visuals

Zekai Shao;Leixian Shen;Haotian Li;Yi Shan;Huamin Qu;Yun Wang;Siming Chen

Year: 2025 | Early Access Article |

StuGPTViz: A Visual Analytics Approach to Understand Student-ChatGPT Interactions

Zixin Chen;Jiachen Wang;Meng Xia;Kento Shigyo;Dingdong Liu;Rong Zhang;Huamin Qu

IEEE Transactions on Visualization and Computer Graphics
Year: 2025 | Volume: 31, Issue: 1 | Journal Article |
The integration of Large Language Models (LLMs), especially ChatGPT, into education is poised to revolutionize students' learning experiences by introducing innovative conversational learning methodologies. To empower students to fully leverage the capabilities of ChatGPT in educational scenarios, understanding students' interaction patterns with ChatGPT is crucial for instructors. However, this e...Show More

StuGPTViz: A Visual Analytics Approach to Understand Student-ChatGPT Interactions

Zixin Chen;Jiachen Wang;Meng Xia;Kento Shigyo;Dingdong Liu;Rong Zhang;Huamin Qu

Year: 2025 | Volume: 31, Issue: 1 | Journal Article |

How Good (Or Bad) Are LLMs at Detecting Misleading Visualizations?

Leo Yu-Ho Lo;Huamin Qu

IEEE Transactions on Visualization and Computer Graphics
Year: 2025 | Volume: 31, Issue: 1 | Journal Article |
In this study, we address the growing issue of misleading charts, a prevalent problem that undermines the integrity of information dissemination. Misleading charts can distort the viewer's perception of data, leading to misinterpretations and decisions based on false information. The development of effective automatic detection methods for misleading charts is an urgent field of research. The rece...Show More

How Good (Or Bad) Are LLMs at Detecting Misleading Visualizations?

Leo Yu-Ho Lo;Huamin Qu

Year: 2025 | Volume: 31, Issue: 1 | Journal Article |

Telling Data Stories with the Hero's Journey: Design Guidance for Creating Data Videos

Zheng Wei;Huamin Qu;Xian Xu

IEEE Transactions on Visualization and Computer Graphics
Year: 2025 | Volume: 31, Issue: 1 | Journal Article |
Data videos increasingly becoming a popular data storytelling form represented by visual and audio integration. In recent years, more and more researchers have explored many narrative structures for effective and attractive data storytelling. Meanwhile, the Hero's Journey provides a classic narrative framework specific to the Hero's story that has been adopted by various mediums. There are continu...Show More

Telling Data Stories with the Hero's Journey: Design Guidance for Creating Data Videos

Zheng Wei;Huamin Qu;Xian Xu

Year: 2025 | Volume: 31, Issue: 1 | Journal Article |

VisTellAR: Embedding Data Visualization to Short-Form Videos Using Mobile Augmented Reality

Wai Tong;Kento Shigyo;Lin-Ping Yuan;Mingming Fan;Ting-Chuen Pong;Huamin Qu;Meng Xia

IEEE Transactions on Visualization and Computer Graphics
Year: 2025 | Volume: 31, Issue: 3 | Journal Article |
Cited by: Papers (1)
With the rise of short-form video platforms and the increasing availability of data, we see the potential for people to share short-form videos embedded with data in situ (e.g., daily steps when running) to increase the credibility and expressiveness of their stories. However, creating and sharing such videos in situ is challenging since it involves multiple steps and skills (e.g., data visualizat...Show More

VisTellAR: Embedding Data Visualization to Short-Form Videos Using Mobile Augmented Reality

Wai Tong;Kento Shigyo;Lin-Ping Yuan;Mingming Fan;Ting-Chuen Pong;Huamin Qu;Meng Xia

Year: 2025 | Volume: 31, Issue: 3 | Journal Article |

PyGWalker: On-the-fly Assistant for Exploratory Visual Data Analysis

Yue Yu;Leixian Shen;Fei Long;Huamin Qu;Hao Chen

2024 IEEE Visualization and Visual Analytics (VIS)
Year: 2024 | Conference Paper |
Exploratory visual data analysis tools empower data analysts to efficiently and intuitively explore data insights throughout the entire analysis cycle. However, the gap between common programmatic analysis (e.g., within computational notebooks) and exploratory visual analysis leads to a disjointed and inefficient data analysis experience. To bridge this gap, we developed PyGWalker, a Python librar...Show More

PyGWalker: On-the-fly Assistant for Exploratory Visual Data Analysis

Yue Yu;Leixian Shen;Fei Long;Huamin Qu;Hao Chen

Year: 2024 | Conference Paper |

From Data to Story: Towards Automatic Animated Data Video Creation with LLM-Based Multi-Agent Systems

Leixian Shen;Haotian Li;Yun Wang;Huamin Qu

2024 IEEE VIS Workshop on Data Storytelling in an Era of Generative AI (GEN4DS)
Year: 2024 | Conference Paper |
Creating data stories from raw data is challenging due to humans' limited attention spans and the need for specialized skills. Recent advancements in large language models (LLMs) offer great oppor-tunities to develop systems with autonomous agents to streamline the data storytelling workflow. Though multi-agent systems have benefits such as fully realizing LLM potentials with decomposed tasks for ...Show More

From Data to Story: Towards Automatic Animated Data Video Creation with LLM-Based Multi-Agent Systems

Leixian Shen;Haotian Li;Yun Wang;Huamin Qu

Year: 2024 | Conference Paper |

Constraint Representation Towards Precise Data-Driven Storytelling

Yu-Zhe Shi;Haotian Li;Lecheng Ruan;Huamin Qu

2024 IEEE VIS Workshop on Data Storytelling in an Era of Generative AI (GEN4DS)
Year: 2024 | Conference Paper |
Data-driven storytelling serves as a crucial bridge for communicating ideas in a persuasive way. However, the manual creation of data stories is a multifaceted, labor-intensive, and case-specific effort, limiting their broader application. As a result, automating the creation of data stories has emerged as a significant research thrust. Despite advances in Artificial Intelligence, the systematic g...Show More

Constraint Representation Towards Precise Data-Driven Storytelling

Yu-Zhe Shi;Haotian Li;Lecheng Ruan;Huamin Qu

Year: 2024 | Conference Paper |

GVVST: Image-Driven Style Extraction From Graph Visualizations for Visual Style Transfer

Sicheng Song;Yipeng Zhang;Yanna Lin;Huamin Qu;Changbo Wang;Chenhui Li

IEEE Transactions on Visualization and Computer Graphics
Year: 2024 | Early Access Article |
Incorporating automatic style extraction and transfer from existing well-designed graph visualizations can significantly alleviate the designer's workload. There are many types of graph visualizations. In this paper, our work focuses on node-link diagrams. We present a novel approach to streamline the design process of graph visualizations by automatically extracting visual styles from well-design...Show More

GVVST: Image-Driven Style Extraction From Graph Visualizations for Visual Style Transfer

Sicheng Song;Yipeng Zhang;Yanna Lin;Huamin Qu;Changbo Wang;Chenhui Li

Year: 2024 | Early Access Article |

Data Playwright: Authoring Data Videos With Annotated Narration

Leixian Shen;Haotian Li;Yun Wang;Tianqi Luo;Yuyu Luo;Huamin Qu

IEEE Transactions on Visualization and Computer Graphics
Year: 2024 | Early Access Article |
Creating data videos that effectively narrate stories with animated visuals requires substantial effort and expertise. A promising research trend is leveraging the easy-to-use natural language (NL) interaction to automatically synthesize data video components from narrative content like text narrations, or NL commands that specify user-required designs. Nevertheless, previous research has overlook...Show More

Data Playwright: Authoring Data Videos With Annotated Narration

Leixian Shen;Haotian Li;Yun Wang;Tianqi Luo;Yuyu Luo;Huamin Qu

Year: 2024 | Early Access Article |

A Survey of Recent Practice of Artificial Life in Visual Art

Zi-Wei Wu;Huamin Qu;Kang Zhang

Artificial Life
Year: 2024 | Volume: 30, Issue: 1 | Journal Article |
Nowadays, interdisciplinary fields between Artificial Life, artificial intelligence, computational biology, and synthetic biology are increasingly emerging into public view. It is necessary to reconsider the relations between the material body, identity, the natural world, and the concept of life. Art is known to pave the way to exploring and conveying new possibilities. This survey provides a lit...Show More

A Survey of Recent Practice of Artificial Life in Visual Art

Zi-Wei Wu;Huamin Qu;Kang Zhang

Year: 2024 | Volume: 30, Issue: 1 | Journal Article |

NFTracer: Tracing NFT Impact Dynamics in Transaction-flow Substitutive Systems with Visual Analytics

Yifan Cao;Qing Shi;Lue Shen;Kani Chen;Yang Wang;Wei Zeng;Huamin Qu

IEEE Transactions on Visualization and Computer Graphics
Year: 2024 | Early Access Article |
Cited by: Papers (1)
Impact dynamics are crucial for estimating the growth patterns of NFT projects by tracking the diffusion and decay of their relative appeal among stakeholders. Machine learning methods for impact dynamics analysis are incomprehensible and rigid in terms of their interpretability and transparency, whilst stakeholders require interactive tools for informed decision-making. Nevertheless, developing s...Show More

NFTracer: Tracing NFT Impact Dynamics in Transaction-flow Substitutive Systems with Visual Analytics

Yifan Cao;Qing Shi;Lue Shen;Kani Chen;Yang Wang;Wei Zeng;Huamin Qu

Year: 2024 | Early Access Article |

Reviving Static Charts into Live Charts

Lu Ying;Yun Wang;Haotian Li;Shuguang Dou;Haidong Zhang;Xinyang Jiang;Huamin Qu;Yingcai Wu

IEEE Transactions on Visualization and Computer Graphics
Year: 2024 | Early Access Article |
Cited by: Papers (4)
Data charts are prevalent across various fields due to their efficacy in conveying complex data relationships. However, static charts may sometimes struggle to engage readers and efficiently present intricate information, potentially resulting in limited understanding. We introduce “Live Charts,” a new format of presentation that decomposes complex information within a chart and explains the infor...Show More

Reviving Static Charts into Live Charts

Lu Ying;Yun Wang;Haotian Li;Shuguang Dou;Haidong Zhang;Xinyang Jiang;Huamin Qu;Yingcai Wu

Year: 2024 | Early Access Article |

ScrollTimes: Tracing the Provenance of Paintings as a Window Into History

Wei Zhang;Wong Kam-Kwai;Yitian Chen;Ailing Jia;Luwei Wang;Jian-Wei Zhang;Lechao Cheng;Huamin Qu;Wei Chen

IEEE Transactions on Visualization and Computer Graphics
Year: 2024 | Volume: 30, Issue: 6 | Journal Article |
Cited by: Papers (1)
The study of cultural artifact provenance, tracing ownership and preservation, holds significant importance in archaeology and art history. Modern technology has advanced this field, yet challenges persist, including recognizing evidence from diverse sources, integrating sociocultural context, and enhancing interactive automation for comprehensive provenance analysis. In collaboration with art his...Show More

ScrollTimes: Tracing the Provenance of Paintings as a Window Into History

Wei Zhang;Wong Kam-Kwai;Yitian Chen;Ailing Jia;Luwei Wang;Jian-Wei Zhang;Lechao Cheng;Huamin Qu;Wei Chen

Year: 2024 | Volume: 30, Issue: 6 | Journal Article |

TacPrint: Visualizing the Biomechanical Fingerprint in Table Tennis

Jiachen Wang;Ji Ma;Zheng Zhou;Xiao Xie;Hui Zhang;Yingcai Wu;Huamin Qu

IEEE Transactions on Visualization and Computer Graphics
Year: 2024 | Volume: 30, Issue: 6 | Journal Article |
Table tennis is a sport that demands high levels of technical proficiency and body coordination from players. Biomechanical fingerprints can provide valuable insights into players’ habitual movement patterns and characteristics, allowing them to identify and improve technical weaknesses. Despite the potential, few studies have developed effective methods for generating such fingerprints. To addres...Show More

TacPrint: Visualizing the Biomechanical Fingerprint in Table Tennis

Jiachen Wang;Ji Ma;Zheng Zhou;Xiao Xie;Hui Zhang;Yingcai Wu;Huamin Qu

Year: 2024 | Volume: 30, Issue: 6 | Journal Article |

Generating Virtual Reality Stroke Gesture Data from Out-of-Distribution Desktop Stroke Gesture Data

Lin-Ping Yuan;Boyu Li;Jindong Wang;Huamin Qu;Wei Zeng

2024 IEEE Conference Virtual Reality and 3D User Interfaces (VR)
Year: 2024 | Conference Paper |
This paper exploits ubiquitous desktop interaction data as an input source for generating virtual reality (VR) interaction data, which can benefit tasks like user behavior analysis and experience enhancement. Time-varying stroke gestures are selected as the primary focus because of their prevalence across various applications and their diverse patterns. The commonalities (e.g., features like veloc...Show More

Generating Virtual Reality Stroke Gesture Data from Out-of-Distribution Desktop Stroke Gesture Data

Lin-Ping Yuan;Boyu Li;Jindong Wang;Huamin Qu;Wei Zeng

Year: 2024 | Conference Paper |

ADPS—A Prescreening Tool for Students With Dyslexia in Learning Traditional Chinese

Ka-Yan Fung;Kit-Yi Tang;Tze Leung Rick Lui;Kuen-Fung Sin;Lik-Hang Lee;Huamin Qu;Shenghui Song

IEEE Transactions on Learning Technologies
Year: 2024 | Volume: 17 | Journal Article |
Prescreening children for specific learning disabilities, e.g., dyslexia, is essential for effective intervention. With a quick and reliable prescreening result, special education coordinators (SENCOs) can provide students with early intervention and relieve their learning pressure. Unfortunately, due to the limited resources, many students in Hong Kong receive dyslexia assessments beyond the gold...Show More

ADPS—A Prescreening Tool for Students With Dyslexia in Learning Traditional Chinese

Ka-Yan Fung;Kit-Yi Tang;Tze Leung Rick Lui;Kuen-Fung Sin;Lik-Hang Lee;Huamin Qu;Shenghui Song

Year: 2024 | Volume: 17 | Journal Article |

Why Change My Design: Explaining Poorly Constructed Visualization Designs with Explorable Explanations

Leo Yu-Ho Lo;Yifan Cao;Leni Yang;Huamin Qu

IEEE Transactions on Visualization and Computer Graphics
Year: 2024 | Volume: 30, Issue: 1 | Journal Article |
Cited by: Papers (1)
Although visualization tools are widely available and accessible, not everyone knows the best practices and guidelines for creating accurate and honest visual representations of data. Numerous books and articles have been written to expose the misleading potential of poorly constructed charts and teach people how to avoid being deceived by them or making their own mistakes. These readings use vari...Show More

Why Change My Design: Explaining Poorly Constructed Visualization Designs with Explorable Explanations

Leo Yu-Ho Lo;Yifan Cao;Leni Yang;Huamin Qu

Year: 2024 | Volume: 30, Issue: 1 | Journal Article |

CommonsenseVIS: Visualizing and Understanding Commonsense Reasoning Capabilities of Natural Language Models

Xingbo Wang;Renfei Huang;Zhihua Jin;Tianqing Fang;Huamin Qu

IEEE Transactions on Visualization and Computer Graphics
Year: 2024 | Volume: 30, Issue: 1 | Journal Article |
Cited by: Papers (4)
Recently, large pretrained language models have achieved compelling performance on commonsense benchmarks. Nevertheless, it is unclear what commonsense knowledge the models learn and whether they solely exploit spurious patterns. Feature attributions are popular explainability techniques that identify important input concepts for model outputs. However, commonsense knowledge tends to be implicit a...Show More

CommonsenseVIS: Visualizing and Understanding Commonsense Reasoning Capabilities of Natural Language Models

Xingbo Wang;Renfei Huang;Zhihua Jin;Tianqing Fang;Huamin Qu

Year: 2024 | Volume: 30, Issue: 1 | Journal Article |

InkSight: Leveraging Sketch Interaction for Documenting Chart Findings in Computational Notebooks

Yanna Lin;Haotian Li;Leni Yang;Aoyu Wu;Huamin Qu

IEEE Transactions on Visualization and Computer Graphics
Year: 2024 | Volume: 30, Issue: 1 | Journal Article |
Cited by: Papers (6)
Computational notebooks have become increasingly popular for exploratory data analysis due to their ability to support data exploration and explanation within a single document. Effective documentation for explaining chart findings during the exploration process is essential as it helps recall and share data analysis. However, documenting chart findings remains a challenge due to its time-consumin...Show More

InkSight: Leveraging Sketch Interaction for Documenting Chart Findings in Computational Notebooks

Yanna Lin;Haotian Li;Leni Yang;Aoyu Wu;Huamin Qu

Year: 2024 | Volume: 30, Issue: 1 | Journal Article |

VideoPro: A Visual Analytics Approach for Interactive Video Programming

Jianben He;Xingbo Wang;Kam Kwai Wong;Xijie Huang;Changjian Chen;Zixin Chen;Fengjie Wang;Min Zhu;Huamin Qu

IEEE Transactions on Visualization and Computer Graphics
Year: 2024 | Volume: 30, Issue: 1 | Journal Article |
Cited by: Papers (5)
Constructing supervised machine learning models for real-world video analysis require substantial labeled data, which is costly to acquire due to scarce domain expertise and laborious manual inspection. While data programming shows promise in generating labeled data at scale with user-defined labeling functions, the high dimensional and complex temporal information in videos poses additional chall...Show More

VideoPro: A Visual Analytics Approach for Interactive Video Programming

Jianben He;Xingbo Wang;Kam Kwai Wong;Xijie Huang;Changjian Chen;Zixin Chen;Fengjie Wang;Min Zhu;Huamin Qu

Year: 2024 | Volume: 30, Issue: 1 | Journal Article |

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