Tools for understanding data require ideas from perception, art, mathematics, as well as the domains that provide the data. In this talk, I will survey a number of different projects that merge these different directions. I will use challenges from biological science and literary studies to motivate our work in data analysis tools. I will describe how we use the study of human perception to shed light on some of the most basic methods of data visualization. I will describe how our collaboration to apply data analysis to literary scholarship inspires new ways to think about visualization. I will describe how this has lead new methods for exploring high-dimensional data that apply machine learning techniques to allow the user to control the exploration of their data.
Michael Gleicher is a Professor in the Department of Computer Sciences at the University of Wisconsin, Madison. Prof. Gleicher is founder of the Department's Computer Graphics group. His research interests span the range of visual computing, including data visualization, image and video processing tools, virtual reality, and character animation techniques for films, games and robotics. Prior to joining the university, Prof. Gleicher was a researcher at The Autodesk Vision Technology Center and in Apple Computer's Advanced Technology Group. He earned his Ph. D. in Computer Science from Carnegie Mellon University, and holds a B.S.E. in Electrical Engineering from Duke University. For the 2013-2014 academic year, he is a visiting researcher at INRIA Rhone-Alpes. Prof. Gleicher is an ACM Distinguished Scientist.
This lecture is organized by the Computer Graphics Group at the Institute of Computer Graphics and Algorithms. Supported by VRVis and the Austrian Computer Society (OCG).