Minsuk Chang

Minsuk Chang

PhD Student in Computer Science @ Georgia Tech

My research interests are in Data Visualization and Human-Computer Interaction, focusing on how humans perceive and interact with visualizations. By exploring this interdisciplinary field, I aim to combine cognitive science with computing to enhance our understanding of human behavior. My goal is to develop a thorough insight into human vision and contribute to designing personalized and adaptive visualizations.

I'm currently a 2nd-year PhD student advised by Dr. Cindy Xiong Bearfield. Before that, I studied Computer Science and Engineering in Seoul National University, South Korea, where I interned at the HCI Lab with Dr. Jinwook Seo.

Research Interests

Data VisualizationBehavior ModelingEye-trackingGraphical PerceptionCognitive Science

News

October 2025

Our paper on visualization literacy and visual attention was accepted to IEEE VIS 2025! See you all in Vienna!

May 2025

Starting my Summer Research Internship at Tableau Research @ Salesforce.

April 2025

Two papers accepted to EuroVis 2025 and VSS 2025.

August 2024

Started my PhD journey at Georgia Institute of Technology, advised by Dr. Cindy Xiong Bearfield.

Selected Publications

Tell Me Without Telling Me: Two-Way Prediction of Visualization Literacy and Visual Attention visualization

IEEE VIS

2025

Tell Me Without Telling Me: Two-Way Prediction of Visualization Literacy and Visual Attention

We trained a bidirectional prediction model that predicts visualization literacy based on visual attention and vice versa.

Grid Labeling: Crowdsourcing Task-Specific Importance from Visualizations visualization

EuroVis

2025

Grid Labeling: Crowdsourcing Task-Specific Importance from Visualizations

We created a new annotation method where users can efficiently label the important area in a visualization.

Early Stage Eye-fixations Reveal Belief-Driven Bias in Correlation Perception visualization

Vision Sciences Society (VSS)

2025

Early Stage Eye-fixations Reveal Belief-Driven Bias in Correlation Perception

We found that early stage eye-fixations show belief-driven bias in correlation perception.

Assessing Graphical Perception of Image Embedding Models using Channel Effectiveness visualization

IEEE VIS

2024

Assessing Graphical Perception of Image Embedding Models using Channel Effectiveness

CLeVer: Continual Learning Visualizer for Detecting Task Transition Failure visualization

IEEE PacificVis

2024

CLeVer: Continual Learning Visualizer for Detecting Task Transition Failure