Main research interest
Data visualization aims to provide insight in large and complex data sets using interactive computer graphics. We develop new methods, techniques, and systems that exploit the unique capabilities of the human visual system, and enable people to interactively explore data. We specifically focus on
- Information visualization: concerning data such as tables, hierarchical data, network data, event data, and combinations of these, and
- Visual analytics: the use of combinations of automated methods (from data mining, machine learning, statistics) and visualization, to deal with even larger data sets.
We take inspiration from and seek challenges in a variety of different application areas, such as health care, software engineering, sports, security, finance, and forensics; and ultimately aim at finding new approaches that are effective for many of these.
Our early work on visualization of large hierarchical data sets led to SequoiaView, a tool for visualizing hard-disks, which was downloaded more than 1M times. Generalization of this approach to business data led to the start-up MagnaView BV, which now for instance provides many high schools in the Netherlands with clear views on their data.
We have done much research on the visualization of network data. The award winning Hierarchical Edge Bundling technique led to the start-up SynerScope BV, which currently provides high end visual analytics technology to a variety of customers in finance and insurance. One highlight was the visualization of telecom traffic in Ivory Coast, where SynerScope and TU/e showed how variations in traffic could be linked to incidents and events in that country
- Sort It Out STW
How to make sense of huge image collections, especially for forensic purposes? We study this in cooperation with UvA and various prospective users.
- SpySpot NWO/STW
We aim to detect sophisticated computer network attacks by developing new visual analytics methods, in cooperation with our colleagues from the Security group and various institutes and companies.
- Philips health care Philips – TU/e flagship
In close cooperation with Philips we study how workflows in health care, especially for radiology and digital pathology, can be visualized and improved.
Furthermore 6 PhD students and one PD are working on various Data Science projects.