Chin Tseng

schoolUniversity of North Carolina at Chapel Hillbar_chart#4045 Global Rank

Total Papers

HCI Rank

#4045

Research Areas

Years Active

Recent Publications

Redundant is Not Redundant: Automating Efficient Categorical Palettes Design Unifying Color & Shape Encodings with CatPAW

Colors and shapes are commonly used to encode categories in multi-class scatterplots. Designers often combine the two channels to create redundant encodings, aiming to enhance class distinctions. However, evidence for the effectiveness of redundancy remains conflicted, and guidelines for constructing effective combina…

CHI '253rd AuthorInteractive Data Visualization +1

Uncovering How Scatterplot Features Skew Visual Class Separation

Multi-class scatterplots are essential for visually comparing data, such as examining class distributions in dimensionality reduction and evaluating classification models. Visual class separation (VCS) measures quantify human perception but are largely derived from and evaluated with datasets reflecting limited types…

CHI '231st AuthorInteractive Data Visualization +2

Measuring Categorical Perception in Color-Coded Scatterplots

Scatterplots commonly use color to encode categorical data. However, as datasets increase in size and complexity, the efficacy of these channels may vary. Designers lack insight into how robust different design choices are to variations in category numbers. This paper presents a crowdsourced experiment measuring how t…

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