Christos Davatzikos, PhD
Christos Davatzikos, PhD is the Wallace T. Miller Sr. Professor of Radiology at the University of Pennsylvania, and Director of the recently founded AI2D Center for AI and Data Science for Integrated Diagnostics. He has been the Founding Director of the Center for Biomedical Image Computing and Analytics since 2013, and the director of the AIBIL lab (AI in Biomedical Imaging). He holds secondary appointments in Electrical and Systems Engineering, Computer and Information Science, and in the Division of Informatics at Penn. He obtained his undergraduate degree by the National Technical University of Athens, Greece in 1989, and his PhD degree from Johns Hopkins, in 1994, on a Fulbright scholarship. He then joined the faculty in Radiology and later in Computer Science, where he founded and directed the Neuroimaging Laboratory. In 2002, he moved to Penn where he founded and directed the section of biomedical image analysis. Dr. Davatzikos’ interests are in medical image analysis. He oversees a diverse research program ranging from basic problems of imaging pattern analysis and machine learning, to a variety of clinical studies of aging and Alzheimer’s Disease, neuropsychiatric disorders, and brain cancer. Dr. Davatzikos has served on a variety of scientific journal editorial boards and grant review committees. He is an IEEE fellow, a fellow of the American Institute for Medical and Biological Engineering, and member of the council of distinguished investigators of the US Academy of Radiology and Biomedical Imaging Research. He was the recipient of the NIA Nathan Schock Lecture award in 2024 and of the DeLeon senior scientist award at the Alzheimer’s International Conference (AAIC) 2025 for his Nature publication “Brain aging patterns in a large and diverse cohort of 49,482 individuals.”
A Q&A with Dr. Davatzikos
- What are the main goals you hope to achieve with your research?
“My research program aims to leverage AI methods to understand complex associations among brain structure and function, clinical, lifestyle, and genetic measures, in aging and dementia.”
- Are there any innovative techniques or technologies that have significantly helped your work?
“AI and image analysis methods have revolutionized the way in which we interpret neuroimaging data and have significantly enhanced our ability to convert brain scans from simple visual objects to rich and quantitative laboratory panels.”
- How important is collaboration in your research? Are you working with any other research groups/centers at Penn?
“Collaboration is critical. In aging and dementia research, but also in research related to neuropsychiatric diseases as well as brain cancer. I work with large international consortia, which provide large and diverse datasets, which are important for AI methods to work. I work with several groups at Penn, including Neuroradiology, Penn Memory Center, Neuropsychiatry, Neurosurgery, and Neuropathology.”
- What’s next for you in terms of future projects or research directions?
“As these AI tools mature, we hope that they will play an important role in next-generation precision diagnostics, by virtue of detecting complex patterns in multi-modal data (imaging, cognition, genetics, lifestyle) that relate to the underlying neuropathologic processes that might be active in an individual patient. Moreover, we hope to be able to detect such patterns well before their clinical manifestation. Toward this goal, we have formed the AI2D Center at Penn.”
Recent Publications:
- Machine learning reveals distinct neuroanatomical signatures of cardiovascular and metabolic diseases in cognitively unimpaired individuals
- Genetic and Clinical Correlates of AI-Based Brain Aging Patterns in Cognitively Unimpaired Individuals
- Neuroimaging endophenotypes reveal underlying mechanisms and genetic factors contributing to progression and development of four brain disorders