Scalable Visual Computing

In the field of Scalable Visual Computing, we invent, improve and apply scalable Machine Learning and AI methods for generating, analyzing, and interacting with visual information.

Research Focus

These methods enable novel applications in the fields of Image Analysis, Computer Vision, Computer Graphics, Visualization and Human-Computer Interaction. This includes applications we develop within ScaDS.AI in the life sciences and environmental sciences.

Computer Vision

In the field of Computer Vision, our goal is to allow humans to incorporate complex structured knowledge into vision algorithms. In the field of Image and Signal Analysis, we focus on image data on different scales and their uncertainty.

Computer Graphics

In the field of Computer Graphics and Visualization, we investigate scalable rendering techniques that enable immersive visual exploration for a fast understanding of complex data.

Human-Computer Interaction

In the field of Human-Computer Interaction for Data Visualization, our research on human-in-the-loop scalability for visual computing will contribute to the interface between AI-empowered systems, Big Data analytics, and various human stakeholders.

Contact

Portrait of Prof. Dr. Bjoern Andres

Prof. Dr. Bjoern Andres

TU Dresden

bjoern.andres@tu-dresden.de

Find out more about our research in the field of AI Algorithms and Methods.

TU
Universität
Max
Leibnitz-Institut
Helmholtz
Hemholtz
Institut
Fraunhofer-Institut
Fraunhofer-Institut
Max-Planck-Institut
Institute
Max-Plank-Institut