Overview

Interactive data exploration is a learning process: users refine their understanding of the data as they inspect visualizations, test hypotheses, and shift attention between attributes and patterns.

This work studies user learning in exploratory data analysis and motivates systems that adapt to changing user understanding rather than treating user intent as fixed.

Research Themes

• User learning during exploratory visual analysis.
• Human-data interaction for adaptive data systems.
• Modeling evolving user intent.
• Interactive data exploration workflows.