Professor Kale researches data visualization and human-computer interaction. He creates and investigates software tools for helping people reason with data and statistical models, especially in situations involving uncertainty. His work seeks to augment human statistical reasoning by providing new ways to interact with data and software tools that more explicitly represent the choices, rationales, values, caveats, and assumptions that underlie data analysis. Current interests include data exploration, model interpretability, causal inference, decision making, fairness, and uncertainty visualization.

Learn more about Professor Kale here.