Dr. Ross Maciejewski: Space, Time and Explainability
Dr. Ross Maciejewski
School of Computing, Informatics & Decision Systems Engineering
Arizona State University
Friday, March 26th at 12:00PM MT
Join the livestream:
Abstract
From smart phones to fitness trackers to sensor-enabled buildings, data is currently being collected at an unprecedented rate. Underlying much of this data are measurements with respect to space and time. However, finding relationships within datasets and accurately representing these spatiotemporal relationships to explain underlying phenomena is a challenging problem. My research addresses fundamental questions of how we can effectively explore spatiotemporal data in order to enhance knowledge discovery, dissemination, and explainability. In this talk, I will reflect on methods in geographic visualization and discuss how computer vision, mathematical topology and information retrieval can be used to support and explain spatiotemporal analyses in crime mapping, urban informatics, and more.
Bio
Ross Maciejewski is an Associate Professor at Arizona State University in the School of Computing, Informatics & Decision Systems Engineering and Director of the Center for Accelerating Operational Efficiency (CAOE) - a Department of Homeland Security Center of Excellence. His primary research interests are in the areas of visual analytics, geography, explainable AI and decision making. Professor Maciejewski is a recipient of an NSF CAREER Award (2014) and was named a Fulton Faculty Exemplar (2017) and Global Security Fellow at Arizona State. His work has been recognized through a variety of awards at the IEEE Visual Analytics Contest (2010, 2013, 2015), a best paper award in EuroVis 2017, and a CHI Honorable Mention Award in 2018.
