The goal of my research is to help more people make sense of complex information, and in particular to reason about uncertainty. Information visualizations leverage perception to summarize data in a cognitively efficient format, making them popular in the media and science. However, many visualizations and other data summaries fail to communicate effectively. One problem is that authors often omit uncertainty information, such as that data are interpreted as being more credible than they are. Another problem is that authors often assume that if the right information--data, statistic, finding etc.--is presented, the audience will naturally trust the presentation and make better decisions.

My research addresses these problems in two ways. First, I use of controlled experiments to identify and model how people reason with data, and in particular uncertainty. Secondly, I create novel interactive tools and techniques that aim to extend and amplify users' abilities to think with data by aligning with their internal representations of complex phenomena.