Scholar

Lin-Ping YUAN

Google Scholar ID: xp3QhPkAAAAJ

Hong Kong University of Science and Technology

AR/VRHuman-computer interactionData Visualization

Citations & Impact

All-time

Citations

324

H-index

i10-index

Publications

Co-authors

list available

Contact

Publications

20 items

Browse publications on Google Scholar (top-right) ↗

Resume (English only)

Academic Achievements

Paper 'Generating Virtual Reality Stroke Gesture Data from Out-of-Distribution Desktop Stroke Gesture Data' accepted by IEEE VR 2024; awarded the 2022 Style3D Graduate Fellowship; won the Deloitte ESG Innovation Award in HackUST 2022 (Top prize under the ESG theme); received over 1M HKD from the General Research Fund, the Research Grants Council (RGC) of Hong Kong, for the research proposal 'Augmenting Situated Visualizations with Tangible User Interfaces'.

Research Experience

Currently a Research Assistant Professor at the Department of Computer Science and Engineering (CSE), The Hong Kong University of Science and Technology (HKUST). Served as a visiting student at the Intelligent Interactive Systems Group, University of Cambridge, supervised by Prof. Per Ola Kristensson. Participated in multiple projects, such as serving as a co-investigator in a project that secured 1M HKD in funding from CORE, HKUST, which will delve into cutting-edge immersive visualization and deep learning techniques to advance the development of a state-of-the-art digital twin of the Greater Bay Area. Also served as an Area Chair of the Computational Interaction Subcommittee for CHI 2025.

Education

Obtained a Bachelor's degree in Software Engineering from Xi’an Jiaotong University (XJTU) in 2019; received a Ph.D. from HKUST VisLab at CSE of HKUST, supervised by Prof. Huamin Qu.

Background

My research interests lie in the intersection of virtual/augmented reality (VR/AR), human-computer interaction (HCI), and data visualization (VIS). I design and develop algorithms, interactive tools, and visual analytic systems to facilitate the creation of various artifacts, including 2D visualizations and infographics, AR data videos, and VR animated stories. Specifically, my research 1) provides computational creativity support by mining design practices from large datasets with deep learning techniques, and 2) adopts a data-driven approach to facilitate creators in understanding and improving the way audience interact with their artifacts.

Miscellany