We conduct research in the following major areas. Please make a selection from the menu below to learn more about research in any of these areas. We also maintain an overview of externally funded projects. A poster with an overview of our work is also available.
We investigate how to visualize medical and biological data. Methodologies such as functional MRI (fMRI), multichannel EEG, and diffusion tensor imaging (DTI) are used to extract functional brain networks and pathways. DNA microarray measurements allow us to visualize regulatory gene networks. We employ insights from perception science to improve current visualization techniques.
Information visualization is used to represent abstract data (such as file system hierarchies, web site or database contents, telecommunication or biological networks, etc.) in a visual way using good visual metaphors and efficient interaction techniques. In our research we focus on the combination of scientific and information visualization techniques in various areas, such as visualization of biological networks or software visualization.
|Software Visualization and Data Mining|
Software visualization methods help understanding and maintaining large and complex code bases by presenting the structure, attributes, and evolution of source code in scalable and intuitive ways. We develop methods that extract various types of information from source code, program traces, and software repositories: dependencies, structure, quality metrics, and developer activity. Next, we develop ways to show the structural evolution of code at class, function, or statement level and that combine the visualization of software architecture diagrams with software metrics defined on groups of diagram elements. We implement our methods in tools that are used on real-world software systems.
|Interactive Computer Graphics|
We investigate how to allow intuitive interaction with rendered images, on large, touch-sensitive displays for single or multiple people. Such direct interaction allows users to be creative and achieve their goals without a limiting interface, and to adapt the graphics and visualizations to their specific needs.
|Non-Photorealistic and Illustrative Rendering|
We combine techniques from computer graphics, visualization, and interactive systems and get inspiration from centuries of traditional illustration. This non-photorealistic rendering breaks free from the traditional (photo-)realism and generates images or animations that use abstraction, exaggeration, and stylization. This increases the freedom of expression and, thus, has great potential for visualization and illustration.
|Multiscale Shape Processing|
Multiscale shape processing involves 2D and 3D shape segmentation, denoising, edge and feature detection, simplification, and matching done on several levels of detail. These operations can be effectively and efficiently supported by several classes of methods, such as skeletonization (or medial axis) computation, level sets, and partial differential equations.
Shape representation is a key ingredient in many research areas and applications, such as Computer Aided Design (CAD), Computer Graphics, but also Finite Elements (FEM) and Isogeometric Analysis (IgA). We focus mainly on representations of (smooth) surfaces of arbitrary manifold topology and on (locally) refinable structures based on splines and/or subdivision, and their use in various application areas. We also investigate methods for converting input meshes into smooth surfaces which can be efficiently rendered on modern GPUs.
Vector graphics, as opposed to raster graphics, represent digital images in a scalable and resolution independent manner, and are based on so-called primitives. These primitives range from simple ones such as lines, circles, disks, and rectangles, to more complicated ones like diffusion curves. We focus on the gradient mesh primitive, available e.g. in Adobe Illustrator and Inkscape, and its extensions, including (gradient) meshes of arbitrary manifold topology, sharp transitions, and local refinement.
!! Major research topics
* Brain visualization
* Software Visualization
* Multiscale skeletons
* Interaction & Graphics
Information visualization is used to represent abstract data in a visual way. It differs from traditional scientific visualization in that the underlying data are not the result of some simulation or measurement of physical (often 3D) data. Examples are: file system hierarchies, contents of a web site or database, telecommunication or biological networks, etc. Finding good visual metaphors and efficient interaction techniques for such abstract data is a major challenge. In our research we focus on the combination of scientific and information visualization techniques in various areas, such as visualization of biological networks or software visualization.