Fabio Egle
Phd Candidate @airob Lab at Department Artificial Intelligence in Biomedical Engineering - AIBE@FAU
Fabio Egle is currently a PhD Candidate at the AIBE@FAU Department of Artificial Intelligence in Biomedical Engineering, involved in the EU Horizon Project - IntelliMan, focusing on biosignal analysis, machine learning, and virtual reality for upper limb prosthesis. Fabio has been active in teaching various seminars and hands-on lab sessions in rehabilitation robotics since January 2022. As the Developer and Founder of helloGreenWorld UG, Fabio is developing a sustainable food app while managing the company part-time since August 2022. Previous experience includes roles as a Working Student in Product Management at Siemens Healthineers, contributing to the development of mobile C-arms, and founding a GbR for mobile app development. Fabio holds a Master of Science in Medical Engineering from FAU Erlangen-Nürnberg and a Bachelor's degree in Industrial Engineering from the University of Bayreuth.
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Department Artificial Intelligence in Biomedical Engineering - AIBE@FAU
The Department Artificial Intelligence in Biomedical Engineering (AIBE) was established as part of the Hightech Agenda Bayern. The traditional chair structure has been abandoned in order to maximize internal exchange and cooperation. Artificial Intelligence research at AIBE is centered around the study and development of intelligent systems in medicine. Our research focuses on theoretical foundations as well as applications for future healthcare. Medical Robotics AIBE is active in all major areas of Medical Robotics, in particular in prosthetics, surgical robotics, rehabilitation robotics and virtual reality for gamification and rehabilitation. We also specifically focus on AI-based co-adaptation of users and devices, and AI-driven human-machine interaction. Imaging and Sensing Our research is dedicated to improving the effectiveness and reducing side effects of medical imaging and sensing technologies. We develop novel diagnostic biomarkers, imaging methodologies, and automated image analysis techniques for early detection of disease and optimal treatment. Health Data Science We advance methodological knowledge in the fields of biostatistics, epidemiology, public health, disease phenotyping, and medical informatics. Our aim is to contribute novel insights from observational health data to provide clinically actionable information for individual patients and to inform health policy on population level. #innovation #FAU #AIBE
