Visualization Group

Visualization has been a major part of the research activities of our Institute over the last 25 years. The vis-group performs basic and applied research projects in all areas of visualization (scientific visualization, information visualization, visual analytics) and visual computing.

Staff

Professors

Scientific Staff

Guest Researchers

Associated Researchers

Stefan Bruckner

Research Areas

Information Visualization and Visual Analytics
In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.
Network Visualization
This research area aims to investigate how to best visualize graph-typed data, both abstractly as well as in domain-specific applications.
Virtual Reality
In this area, we focus on user experiences and rendering algorithms for virtual reality environments, including methods to navigate and collaborate in VR, foveated rendering, exploit human perception and simulate visual deficiencies.
Biological Data Visualization
In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.
Medical Visualization
This research area bridges the gap between visualization and medicine by providing comprehensible visual means to detect diseased regions or to aid clinical treatment decisions.
Perception
In this area, our research focuses on understanding and using the capabilities of human perception for designing high-quality graphics algorithms and effective visualizations.
Illustrative Visualization
In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.
Visualization in The Material Sciences
This research is directed towards visual parameter space analysis, 4D analysis of time varying XCT data, visual analytics of segmentation ensembles, comparative visualization of volume ensembles as well as parameter space analysis of segmentation pipelines.