We aim for excellence in transforming novel ideas
into successful research projects and into technology innovations,
which contributes to improving quality of life.
We are interested in designing, developing, and evaluating
user interfaces and interaction techniques
to help users solve their challenging problems in everyday life.
Designing intuitive interfaces and interaction techniques that enhance user experience and productivity across diverse computing platforms.
Exploring how people interact with data through visualization, analytics tools, and interactive systems to support decision-making.
Investigating how humans and AI systems can collaborate effectively, focusing on user-centered AI design.

Fields, Bridges, and Foundations: How Researchers Browse Citation Network Visualizations
What are the specific elements researchers want to see in a citation network?

Natural Language Dataset Generation Framework for Visualizations Powered by Large Language Models
a Large Language Model (LLM) framework that generates rich and diverse NL datasets using only Vega-Lite specifications as input

LitWeaver
Supporting Novice Researchers to Write Literature Review using Language Models

Enhancing Data Literacy On-demand: LLMs as Guides for Novices in Chart Interpretation
Chart reading guidance using LLM through both textual and visual annotations

PhenoFlow
A Human-LLM Driven Visual Analytics System for Exploring Large and Complex Stroke Datasets

CLAMS
A Cluster Ambiguity Measure for Estimating Perceptual Variability in Visual Clustering
News
View All
Jun 15
Hyeon's short paper on exploring DR literature is accepted for publication in EuroVis 2025.
Apr 08
Hyeon's full paper on clustering validation is accepted for publication in IEEE TPAMI.
Jan 17
Two papers have been accepted to ACM CHI 2025!
Nov 11
Congratulations!! Hyeon has been selected as a recipient for the Google Ph.D. Fellowship!!
Jul 16
Jaeyoung's full paper "PhenoFlow" will appear in IEEE VIS 2024.