(734) 763-2285
Applications: Behavioral Science, Computer Science, Human Subjects Trials and Intervention Studies, Research Reproducibility, Social Sciences, Survey Research Methodologies: Bayesian Methods, Data Visualization, Decision Science, Human-Computer Interaction, Statistical Inference, Statistical Modeling, Statistics Relevant Projects:

Health Data Exploration Project, Google

Matthew Kay

Assistant Professor, School of Information

Affiliation(s):

Computer Science and Engineering, College of Engineering

Matthew Kay, PhD, is Assistant Professor of Information, School of Information and Assistant Professor of Electrical Engineering and Computer Science, College of Engineering, at the University of Michigan, Ann Arbor.

Prof. Kay’s research includes work on communicating uncertainty, usable statistics, and personal informatics. People are increasingly exposed to sensing and prediction in their daily lives (“how many steps did I take today?”, “how long until my bus shows up?”, “how much do I weigh?”). Uncertainty is both inherent to these systems and usually poorly communicated. To build understandable data presentations, we must study how people interpret their data and what goals they have for it, which informs the way that we should communicate results from our models, which in turn determines what models we must use in the first place. Prof. Kay tackles these problems using a multi-faceted approach, including qualitative and quantitative analysis of behavior, building and evaluating interactive systems, and designing and testing visualization techniques. His work draws on approaches from human-computer interaction, information visualization, and statistics to build information visualizations that people can more easily understand along with the models to back those visualizations.