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.
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.
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.
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.
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.