Professor Scheuermann will present two topics in his talk:

Topological Visualization of Uncertain Scalar Fields and Climate research

While the topological analysis and visualization of scalar field data is well established, applications like climate research ask for an analysis of uncertain field data like ensembles of scalar fields. In this talk, we show how this problem can be tackled and that the solution allows for new insights into climate simulations. Especially, we consider the North Atlantic Oscillation (NAO), the strongest single factor for European winter weather.

Computer Assisted Stroke Therapy using Neural Networks

Stroke is one of the three most often causes of death in western countries. Any therapy is highly time-critical, relying on making correct decisions upon surgery within a short time frame. We show how deep artificial neural network can help neurologists to decide whether they should perform endovascular thrombectomy to remove a blood clot from the blocked blood vessel in stroke patients. We show the results of different neural networks using a general linear model as baseline.


Gerik ScheuermannGerik 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. He became a full professor at the Institute of Computer Science at the Universität Leipzig in 2004. 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.