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Feature Oriented Visualization

Talk by Prof. Dr. Gerik Scheuermann, Universität Leipzig, Institute for Computer Science

Climate simulations and computational fluid dynamics are major sources of simulation data sets. The interpretation of these data relies to a large extend on effective visualization methods. As the data is often too large for direct visualization, data reduction methods like feature detection or topological structure extraction are a promising route. We present several topologically motivated approaches to detect relevant structures in computational fluid  dynamics simulations that might also be suitable in climate research. In addition, we discuss recent work on using moments to find patterns in velocity vector fields.

CV: Gerik Scheuermann received a PhD in computer science from TU Kaiserslautern in 1999. After postdoctoral work at UC Davis, he returned to Kaiserslautern as a junior professor in 2001. After declining professorships at the Universität Freiburg and Universität Jena, he became a full professor at the Institute of Computer Science at the Universität Leipzig in 2004. He also declined an offer to become a professor at Universität Mainz in 2009. His research interests center around all areas of visualization including visual analytics. He has also worked on Clifford algebra, topological data analysis, and information theoretic methods. He published more than 180 papers on these topics. He served as Paper Co-Chair for EuroVis 2008, IEEE SciVis 2011, IEEE SciVis 2012. and IEEE PacificVis 2015. He co-organized TopoInVis 2007, AGACSE 2008, EuroVis 2013, and the Dagstuhl 2014 Seminar on Scientific Visualization.  Furthermore, he is currently speaker of the GI working group on visualization, GI VIS.

Slides: pdf

DKRZ, Seminar room 034, Wednesday 10.02.2016, 14:15


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