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Minsuk Chang

My research field is Data Visualization and Human-Computer Interaction, understanding and supporting how humans perceive and interact with data. I try to combine cognitive science and computing to better support human-AI interaction.

I'm currently a 3rd-year PhD student advised by Cindy Xiong Bearfield. I've also interned at Tableau Research @ SalesforceSalesforce logo in Summer 2025, where I worked with Srishti Palani and Arjun Srinivasan. This summer, I'm interning at LG AI Research, working with Bumsoo Kang, Jiyong Cho, and Moontae Lee.

Research Interests

Data VisualizationHuman-AI InteractionEye-trackingDecision-Support SystemsCognitive Science

Interactive demos

News

  • July 2026

    Our paper on channel effectiveness and graphical perception was accepted to IEEE VIS 2026 as a full paper!

  • July 2026

    I gave an invited talk at the HCI Lab at Seoul National University.

  • May 2026

    Starting my internship at LG AI Research this summer.

  • April 2026

    I successfully passed my CS PhD qualifying exam!

  • February 2026

    The AI-Based Literacy Score Prediction Model is now open! Visit the Literacy Test page to check whether you are expert or novice in visualization literacy.

  • January 2026

    Our paper on decision-making and critical thinking was accepted to ACM IUI 2026! See you in Paphos!

  • October 2025

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

Show earlier news
  • 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 Tech, advised by Dr. Cindy Xiong Bearfield.

  • February 2024

    Our paper on assessing graphical perception was accepted to IEEE VIS 2024.

  • January 2024

    Paper on continual learning visualization accepted to IEEE PacificVis 2024.

Selected Publications

ACM IUI

2026

Criticality: Scaffolding Decision-Making with Interactive Critical Thinking and Evidence-Based Reasoning Traces

We introduce Criticality, a system that operationalizes the Paul-Elder Critical Thinking framework to structure reasoning into interactive elements and grounds claims in verifiable evidence.

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.

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.

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.

IEEE VIS

2024

Assessing Graphical Perception of Image Embedding Models using Channel Effectiveness

We assessed how well image embedding models perceive visual encoding channels in charts, comparing their accuracy and discriminability against human graphical perception.

IEEE PacificVis

2024

CLeVer: Continual Learning Visualizer for Detecting Task Transition Failure