Prof. Dr. Philipp Fürnstahl
Area of Research
Description of Research Interest
My research lies at the intersection of AI, robotics, surgical data science and orthopedic surgery. A key enabler is OR-X, a national research infrastructure that supports advanced experimentation and will be pivotal for developing intelligent intraoperative systems.My work spans three larger areas. The first focuses on multimodal sensing, developing approaches that combine visual, acoustic, positional and imaging signals into coherent representations of the surgical scene. The goal is to approximate the richness of human intraoperative perception and to provide robust input for intelligent systems.
The second area centers on multimodal perception and scene understanding. I design AI methods that interpret anatomy, workflow and tool tissue interactions. This work converges in the development of surgical digital twins, which provide high-fidelity spatiotemporal models.
The third area focuses on system intelligence in computer- and robot-assisted surgery, including adaptive navigation, augmented reality, autonomous behaviors and data-driven decision support. My long-term aim is to build systems that understand surgical context deeply and act with greater autonomy, reliability and clinical relevance.
Special Expertise
- Computer-assisted and robotic surgery
- Intraoperative Artificial Intelligence
- Surgical Data Science
- Augmented Reality
- Pre-clinical validation
Shareable Platforms, Services, Equipment & Infrastructure
Our research is closely connected with the OR-X, a national research infrastructure included in the Swiss Roadmap for Research Infrastructures. The OR-X connects a highly realistic surgical environment with cutting-edge research infrastructure including high-performance network and AI servers, intraoperative imaging devices, data capturing systems, and different surgical navigation and robotics systems.
Member of Collaborative/interdisciplinary Research Consortia
- OR-X Swiss Roadmap for Research Infrastructures
- UMZH Flagship project SURGENT - Surgeon Enhancing Technologies
- InnoSuisse Flagship project PROFICIENCY - AR and AI driven surgical training of the future
University Hospital Balgrist