Research
The krueger lab designs and develops scalable visual analytics approaches. Visual analytics is an emerging research field to tackle big data analysis challenges. It creates added value by combining the processing power and accuracy of machines with human capabilities to perceive information visually. Automatic means (machine learning and KDD) are used to aggregate and classify data and to detect hidden patterns. Interactive visualizations allow to explore and query the data and to steer automatic processes with domain knowledge. This increases trust in data, models, and results, which is especially important when critical decisions need to be made. The strengths of visual analytics have been shown to be particularly advantageous when problems and goals are underspecified and exploratory means are needed to discover yet unknown patterns. The krueger lab especially focuses on visualization and analytics of large imaging data as it appears in biological, biomedical, and geographical contexts.
Below is a list of former publications in the field which will be updated with lab publications once the lab has officially started.