U.S. Department of Energy

Pacific Northwest National Laboratory

Applying Topology In Visualization: From Atmospheric Phenomena to Battery Materials

Wednesday, May 17, 2017
Dr. Bei Wang
Assistant Professor, School of Computing
University of Utah
In this talk, I will describe a few recent research activities involving the application of topology in data analysis and visualization. First, I will describe how we can enable atmospheric scientists to extract and track pressure-perturbation events both spatially and temporally to better understand atmospheric phenomena using tracking graphs. Second, I will review our design process in building analysis and visualization capabilities for ALMA data cubes  in astronomy using contour trees. Finally, I will discuss briefly new approaches using discrete Morse theory and Delaunay triangulation to study properties of carbon based battery materials.
Speaker Bio

Dr. Bei Wang is an assistant professor at the School of Computing, and a faculty member at the Scientific Computing and Imaging Institute, University of Utah. She received her Ph.D. in Computer Science from Duke University. Her research expertise lies in the theoretical, algorithmic, and application aspects of data analysis and data visualization, with a focus on topological techniques.

Her research interests include theoretical and algorithmic aspects in computational topology and computational geometry; foundations, techniques and applications for scientific data analysis and visualization; computational biology and bioinformatics; machine learning; and data mining.

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