Research groups

The focus of the group is on multi- and high-dimensional data which is in many cases time-dependent. The group’s goal is to help users acquire new insights and increased decision confidence by enabling an interactive dialogue with big structured data. For this purpose, the researchers of the Visual Analytics group create novel technologies which combine visualization, user interaction, and automatized analysis methods such as data mining with response in real-time. The application domains of current projects comprise, e.g., the energy sector, industrial manufacturing, health policymaking, and simulation-based development of powertrain systems.

The research of our Visual Analytics group focuses on creating effective visual techniques for supporting tasks along the process of data analysis:

• Data quality assessment and cleansing of complex data, e.g., by visualizing plausibility checks
• Getting an overview of high-dimensional data and recognizing dependencies in this data
• Building and validating regression models, e.g., predictive models of energy time series as well as surrogate models of time-consuming physical simulations
• Multi-criteria decision making, e.g., for supporting statistical model selection as well as for decisions in engineering

An additional research topic concerns the creation of highly responsive software infrastructures which provide immediate feedback on user interaction even in case of large data. In this context, the research group focusses on tightly integrating popular analytical platforms such as Matlab, R, and Python, as well as on defining flexible modules which permit rapid prototyping of task-specific analytical applications.