Nov 2, 2018
Lopata Hall, Room 101
Visualizing Scalar Data with Computational Topology and Machine Learning
In this talk, I will discuss and demonstrate two visualization projects. The first is recent work with collaborators at UPMC Sorbonne on the creation of the Topological ToolKit (TTK), an open source software platform for topological data analysis of piecewise linear scalar fields. TTK is built on top of VTK and ParaView, and provides access points for developers, end users, and researchers across a wide of range of experience levels. Two key advantages of TTK are that it (1) provides a unified platform for topological analysis, allowing a modular approach to analyzing data under a consistent set of mathematical abstractions and (2) offers an efficient triangulation data structure that caches queries for repeated use. TTK is available on the web at https://topology-tool-kit.github.io/
In the second part of my talk, I will describe a new project with collaborators at Vanderbilt University that studies how generative models can be used to model the process of volume rendering scalar fields. We construct a generative adversarial network that learns the mapping from volume rendering parameters, such as viewpoint and transfer function, to the rendered image. In doing so, we can analyze the volume itself and provide new mechanisms for guiding the user in transfer function editing and exploring the space of possible images that can be volume rendered. Both our training process and applications are available on the web at https://github.com/matthewberger/tfgan
Joshua A. Levine (https://www.cs.arizona.edu/~josh) is an assistant professor in the Department of Computer Science at University of Arizona. Prior to starting at Arizona in 2016, he was an assistant professor at Clemson University from 2012 to 2016, and before that a postdoctoral research associate at the University of Utah's SCI Institute from 2009 to 2012. He received his PhD in Computer Science from The Ohio State University in 2009 after completing BS degrees in Computer Engineering and Mathematics in 2003 and an MS in Computer Science in 2004 from Case Western Reserve University. His research interests include visualization, geometric modeling, topological analysis, mesh generation, vector fields, performance analysis, and computer graphics.