Shadi Albarqouni

Shadi Albarqouni is a W2 Professor of Computational Imaging Research at the University Hospital Bonn, AI Young Investigator Group Leader at Helmholtz Munich, and Senior Research Affiliate at TU Munich. His roles include leading research in medical imaging, computational procedures, and artificial intelligence in healthcare. He holds a PhD in Informatics from Technical University Munich (2017) under Prof. Nassir Navab, with prior academic experience as a lecturer and postdoctoral researcher.

Education:

• PhD Informatics (2013-2017), Technical University Munich
• M.Sc. Electrical Engineering (2005-2010), Islamic University of Gaza
• B.Sc. Electrical Engineering (2001-2005), Islamic University of Gaza

Research Interests:

• Medical Image Analysis (e.g., segmentation, anomaly detection)
• Deep Learning applications in healthcare
• Generative models and computer vision
• Surgical robotics and augmented reality
• Federated learning for medical data

Publications: Over 30 peer-reviewed articles focusing on medical imaging, including works on GANs for skin lesion synthesis, federated learning algorithms, and MRI anomaly detection. Recent trends emphasize interdisciplinary approaches combining AI with clinical challenges.

Awards:

• Best Paper Award at MIAR 2016
• Reviewer Commendation at MICCAI 2018
• DAAD PRIME Fellowship

Advising/Grants: Leads research groups focusing on AI in healthcare and collaborates internationally. Manages projects on federated learning and medical data challenges. His lab at University Hospital Bonn focuses on computational imaging and surgical data science.

Labs/Teams: Director of labs at University Hospital Bonn (Department of Diagnostic and Interventional Radiology), Helmholtz Munich, and TU Munich. Active in interdisciplinary teams like RobUSt (Robotics and Ultrasound) and NARVIS (Navigation and Visualization).