The research at the "Intelligent Sensing and Perception" Department emphasizes the development of data-efficient, domain-invariant, and privacy-preserving algorithms to perceive humans and understand their interactions with their surroundings, including their behavior, emotions, physiology, intentions, and needs.
Our main research topics include:
- Deep Learning for Human Activity Analysis
- Learning with Less: Resource- and Data-efficient Recognition, Privacy-preserving Visual Recognition
- Open Set and Open Domain Recognition, Uncertainty-aware Recognition in Changing Environments
- Computer Vision for Robotics and Assistive Systems
- Intelligent Vehicles
- Applications for Health Monitoring, Physiological Analysis and Medical Diagnostics
Interest in researching with us?
For further information regarding our thesis topics and how you can do research with us, you are welcome to contact us directly via email.
Alina Roitberg
Jun.-Prof Dr.-IngDirector