Matthew Kay, PhD, MS
Assistant Professor of Information, School of Information and Assistant Professor of Electrical Engineering and Computer Science, College of Engineering
"Uncertainty visualization using discrete outcomes"
Abstract: Understanding uncertainty is necessary to make informed decisions from predictions: If my bus is predicted to arrive 10 minutes from now, what is the chance it actually shows up in 5 minutes—and more importantly, do I have time to get a coffee? I will outline a generalized approach to uncertainty visualization—discrete outcomes—that has found success in many contexts, including medical risk communication and hurricane path prediction, and give examples from my own work in transit arrival time prediction.