Carl Moons is professor of Clinical Epidemiology and former director of research at the Julius Center, UMC Utrecht. He is also figure head Artificial Intelligence for Health of the UMC Utrecht and Utrecht University, developed the AI strategy of the UMC Utrecht and established 5 dedicated AI labs (AI Living Technologies and Regenerative Medicine; AI Molecular Medicine; AI Imaging and Imaging guided interventions; AI Methods and Fundamentals; AI Healthy Living and Prevention).

He has directed and co-written the development of an international quality guideline for introduction of safe and effective AI in Healthcare which has been adopted in various countries. He leads two large international consortia which develop guidelines for AI in Healthcare: the TRIPOD+AI guideline for transparent and explainable reporting of AI in healthcare; and the PPROBAST+AI guideline on the assessment of quality and validity of AI algorithms in healthcare.

His scientific career (>750 peer reviewed publications, books and book chapters) focuses on research on the methods for the evaluation and introduction of medical innovations, ranging from medical drugs, robotics, tests, eHealth and AI-algorithms. He is principal investigator in numerous international clinical (epidemiology) studies funded by various national and international organisations (EU, NHS, NIH). His experience covers the full range of conduct, data analysis, reporting and dissemination of such studies, varying from studies on the evaluation of medical devices and tests for diagnosis, prognosis, screening and monitoring, to etiological studies and randomised therapeutic trials, to meta-epidemiological studies, both on aggregate and individual participant data. His main focus concerns improving the methods and approaches for evaluation and implementation of medical devices, (bio)markers and prediction models. His major expertise is introducing innovations for the design, conducting, analysis and reporting of evaluations of diagnostic and prognostic tests, devices, (bio)markers and prediction models. Clinical topics include cancer, deep vein thrombosis, stroke, heart failure and peri-operative risk assessment. He teaches graduate and postgraduate students in all aspects of clinical (epidemiological) research design, conducting, analysis and reporting, throughout the world.