I am currently a research intern advised by Prof. Xiaojuan Ma at Hong Kong University of Science and Technology, focusing on immersive analytics of oceanographic data. I am also a MCs student at ShanghaiTech University, supervised by Prof. Quan Li
I am with an open mind to explore my research potential in diverse avenues during my MCs study. Thus, I have dived into areas of Visual Analytics, Hybrid User Interface, Theories/Methodologies, and VR/AR. Through this diverging process, I am delighted to finally converge on my research interest - Facilitating enhanced human interaction, analysis, and overall well-being in extended reality through the integration of visualization and intelligence , which prompts me to
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Yuchen Wu, Shenghan Gao, Shizhen Zhang, Xiaofeng Dou, Xingbo Wang, Quan Li
IEEE Transactions on Visualization and Computer Graphics (TVCG) 2025 TVCG 2025
We formulated refined topologies for data, requirements, and solutions. We propose conceptualizing the connections between requirements, data, and solutions through knowledge graphs and utilizing solution paths to encapsulate fundamental problem-solving knowledge in visual analytics research. Through the consolidation of solution paths into a graph and analyzing their interconnections, we discerned a subset of problem-driven design patterns that demonstrated the efficacy of our approach.
Yuchen Wu, Shengxin Li, Shizhen Zhang, Xingbo Wang, Quan Li
International Symposium of Chinese CHI 2024 ChineseCHI 2024Best Paper
We introduce Trinity, a hybrid mobile-centric delivery support system that provides guidance for multichannel delivery on-the-fly. On the desktop side, Trinity facilitates script refinement and offers customizable delivery support based on large language models (LLMs). Based on the desktop configuration, Trinity App enables a remote mobile visual control, multi-level speech pace modulation, and integrated delivery prompts for synchronized delivery.
Yuchen Wu, Yuansong Xu, Shenghan Gao, Xingbo Wang, Wenkai Song, Zhiheng Nie, Xiaomeng Fan, Quan Li
IEEE Transactions on Visualization and Computer Graphics (TVCG) 2023 VIS 2023
This study identified computational features, formulated design requirements, and developed LiveRetro , an interactive visual analytics system. It enables comprehensive retrospective analysis of livestream e-commerce for streamers, viewers, and merchandise. LiveRetro employs enhanced visualization and time-series forecasting models to align performance features and feedback, identifying influences at channel, merchandise, feature, and segment levels.