Ardit Ramadani

Ardit Ramadani is a Postdoctoral Researcher at Deutsches Herzzentrum München (German Heart Center Munich) and affiliated with the Technical University of Munich's Department of Informatics, Chair of Computer Aided Medical Procedures (Prof. Navab). His work bridges medical image analysis, computer vision, and surgical robotics to advance minimally invasive cardiac interventions through computational solutions.

His educational background includes:

• Doctor of Natural Sciences in Computer Science - Biomedical Computing (2019-2025), Technical University of Munich
• Master of Science in Biomedical Computing (2015-2018), Technical University of Munich
• Bachelor of Science (Hons) in Computer Science (2012-2015), University of Sheffield, International Faculty CITY College, Thessaloniki

Ramadani specializes in multimodal catheter tracking systems, developing novel approaches for electromagnetic, image-based, and active-element tracking combined with shape sensing and hybrid methodologies. His research addresses critical challenges in registration accuracy and motion compensation during endovascular procedures, with direct applications in cardiac interventions requiring real-time spatial precision.

His 2022-2023 publications reveal a concentrated research trajectory in catheter tracking innovation, particularly focusing on electromagnetic tracking enhanced by bioelectric sensing and dynamic time warping algorithms. These works demonstrate strong integration of computer vision with medical robotics, targeting motion artifacts in cardiac environments through multimodal data fusion and robust registration frameworks applicable to ultrasound and preoperative imaging.

No scientific awards were documented in the provided materials.

Ramadani actively supervises student projects in multimodal catheter tracking, minimally invasive endovascular procedures, and motion-compensation techniques. He contributes to the DHM Research Group and RobUSt (Robotics and Ultrasound) lab, developing surgical data science solutions for cardiac interventions while teaching advanced courses in medical image computing and surgical robotics at TUM.