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Tino Weinkauf

Professor of Visualisation

Analysing large, multidimensional amounts of data is a challenging task. It is ideally done using advanced tools that make it possible to concentrate on the most relevant information and to automate the analysis. This can be achieved by using what is known as function-based methods, which promote targeted studies of the most important aspects of an amount of data.
Tino Weinkauf and his research team develop algorithms and mathematical models to visualise batches of data from a number of different areas such as fluid dynamics, planetology and cell biology. The research team’s objective is to develop solutions to various visualisation problems with the purpose of enabling visual analysis for a large number of practical applications, especially when very large volumes of data are involved. One of the greatest challenges today is that the amount of simulation data becomes so large that it is almost impossible to save, which strongly impedes the subsequent data analysis including classical visualisation. Weinkauf’s research team addresses this by letting at least part of the data analysis to be done by the super computer, which is run next to the simulation.
The research is conducted in cooperation with many international research teams at, for example, the Max-Planck-Institute for Informatics and the University of Magdeburg in Germany.

Belongs to: About KTH
Last changed: Dec 22, 2015
Joachim Oberhammer
Viktoria Martin
Yen-Hsi Tsai
Tino Weinkauf
Stefan Hrastinski
Sebastiaan Meijer
Roberto Bresin
Patrik Henelius
Örjan Smedby
Muhammet S. Toprak
Mathias Ekstedt
Leif Dahlberg
Joydeep Dutta
Henrik Hult
Hans Westlund
Felix Ryde
Ayşe Ataç Nyberg
Cecilia Williams