Practical machine learning approaches for medical image computing

Marc Niethammer is a Professor of Computer Science and Engineering, as well as Neurological Surgery, at the University of California, San Diego (UCSD). He holds the Halıcıoğlu Endowed Chair in Health AI. Dr. Niethammer’s research lies at the intersection of medicine and machine learning, focusing on designing computational algorithms to extract quantitative measures from medical data, often involving images. His work includes approaches for image segmentation, image registration, shape analysis, imaging biomarkers, and general multi-modal models. His work is highly interdisciplinary, heavily motivated by driving biomedical problems, and, consequently, spans the full range from developing general computational methods to applications directly relevant to biomedical research and clinical care. Before joining UCSD, he was a Professor of Computer Science at the University of North Carolina at Chapel Hill (UNC) from 2008 to 2024, where he led the Biomedical Image Analysis Group. Dr. Niethammer joined UNC after completing postdoctoral training at Harvard Medical School/Brigham and Women's Hospital. He holds a Ph.D. in Electrical and Computer Engineering from the Georgia Institute of Technology (Georgia Tech), along with M.Sc. degrees in Applied Mathematics and Engineering Science and Mechanics from Georgia Tech. Additionally, he holds a Diplom Ingenieur degree in Engineering Cybernetics from the University of Stuttgart, Germany.