Hi, I'm Yuchen Wu

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

look for a Ph.D. position with prospective admission in Fall 2025! Kindly e-mail me if you see a good fit!
Curriculum Vitae

Education
  • ShanghaiTech University
    ShanghaiTech University
    Master Student in Computer Science (MCs)
    Sep. 2022 - present
Experience
  • Hong Kong University of Science and Technology
    Hong Kong University of Science and Technology
    Research Intern
    Sep. 2024 - present
News
2025
Our paper about problem-driven design pattern in VA is accepted by TVCG! Visit the website for more info! Website
Feb 02
2024
Our paper is accepted to ChineseCHI with 🏆 Best Paper Award (0.6%), big thanks to my collaborators!
Nov 22
Become a research intern at HCI Initiative @ HKUST, working with Prof. Xiaojuan Ma!
Sep 30
Our paper accepted by TVCG! Congrats to my collaborators.
Jan 30
2023
Attending VIS 2023 at Melbourne!
Oct 23
Two papers accepted at VIS 2023!
Jun 28
2022
Begin my MCS journey at ViSeer Lab with Prof. Quan Li!
Aug 31
Selected Publications (view all )
From Requirement to Solution: Unveiling Problem-Driven Design Patterns in Visual Analytics
From Requirement to Solution: Unveiling Problem-Driven Design Patterns in Visual Analytics

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.

From Requirement to Solution: Unveiling Problem-Driven Design Patterns in Visual Analytics
From Requirement to Solution: Unveiling Problem-Driven Design Patterns in Visual Analytics

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.

Trinity: Synchronizing Verbal, Nonverbal, and Visual Channels to Support Academic Oral Presentation Delivery
Trinity: Synchronizing Verbal, Nonverbal, and Visual Channels to Support Academic Oral Presentation Delivery

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.

Trinity: Synchronizing Verbal, Nonverbal, and Visual Channels to Support Academic Oral Presentation Delivery
Trinity: Synchronizing Verbal, Nonverbal, and Visual Channels to Support Academic Oral Presentation Delivery

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.

LiveRetro: Visual Analytics for Strategic Retrospect in Livestream E-Commerce
LiveRetro: Visual Analytics for Strategic Retrospect in Livestream E-Commerce

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.

LiveRetro: Visual Analytics for Strategic Retrospect in Livestream E-Commerce
LiveRetro: Visual Analytics for Strategic Retrospect in Livestream E-Commerce

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.

All publications