We know imaging.

Rashindra Manniesing is the Founder and CEO of XDMD. He holds a master’s degree in Electrical Engineering from Delft University of Technology and a PhD in Medical Image Analysis from Utrecht University. He is an internationally recognized expert in neurovascular imaging with over 70 publications in top journals and conference proceedings. Before founding XDMD, he co-founded a company building evidence-based search and worked as an independent scientific advisor in medical imaging. Dr. Manniesing solves hard engineering problems, and is able to balance attention to detail with long-term vision.

Gastón Creci is the AI software engineer of XDMD. He holds a master’s degree in Theoretical Physics and a PhD in Gravitation from Utrecht University. With a fruitful career in physics, his programming skills and expertise in analytical and numerical modeling provide a solid foundation for developing robust AI-driven medical imaging solutions.

Chris de Korte is a full professor of ultrasound imaging at Radboudumc and the University of Twente, a registered medical physicist, and chair of the Medical Ultrasound Imaging Center (MUSIC) at Radboudumc, The Netherlands. He holds a master’s degree in Electrical Engineering from Eindhoven University of Technology and a PhD in Medical Sciences from Erasmus University Rotterdam. His research focuses on functional ultrasound imaging for cardiovascular and oncological applications, securing over €10M in research funding, including prestigious personal NWO grants (VENI, VIDI, VICI). He has authored over 220 publications and has delivered numerous invited and keynote lectures. He is president of the Netherlands Society for Medical Ultrasound and general chair of the 2025 IEEE International Ultrasonics Symposium. Prof. de Korte has a strong drive to innovate, guided by reasoning from first principles and pushing his field forward to improve patient care.

Jonas Teuwen is group leader of the AI for Oncology Lab at the Netherlands Cancer Institute, where he leads a team of over 20 researchers working at the intersection of AI, immunology, and medical imaging. He holds a master’s degree in Applied Mathematics from the University of Massachusetts and Delft University of Technology, and a PhD in Pure Mathematics and Applied Physics from Delft University of Technology. His work focuses on developing clinically robust AI systems to advance cancer diagnosis and treatment. He has secured over €10M in funding and authored over 100 publications. Previously he served as CTO of Ellogon.AI where he led the development of diagnostic AI tools and steered regulatory certification efforts. Prof. Teuwen combines rare depth in both fundamental and applied AI with exceptional technical skill, bringing world-class expertise to oncology and medical imaging.

Professor Marcel van Gerven heads the Artificial Cognitive Systems lab in the Department of Machine Learning and Neural Computing of the Donders Institute for Brain, Cognition and Behaviour. He is also director of the Nijmegen ELLIS unit and ELLIS Fellow. His research focuses on bridging the gap between artificial and natural intelligence using techniques which have their roots in machine learning and neuromorphic computing. He is a Vidi laureate and recipient of several national and international grants and has authored over 240 publications.

Thijs Vande Vyvere is a specialized neuroanatomist and neuroscientist, guest professor at the University of Antwerp, and senior researcher at Antwerp University Hospital, Belgium. He holds a master’s degree in Biomedical Sciences and a PhD in Medical Sciences with a focus on Neuroradiology from the University of Antwerp, Belgium. His research centers on advanced anatomical imaging of the (damaged) brain. With over 60 publications in the field of traumatic brain injury, he has extensive expertise in medical image interpretation, segmentation, and annotation, and he has played a key role in developing ground truth datasets for AI-driven algorithms. Prof. Vande Vyvere combines a meticulous eye for detail with a commitment to deeply understanding what we see in a medical image.