Dr. Miao's research focuses on developing methods to learn interpretable patterns and mechanisms for population and individual health improvement. His expertise spans clinical trial design, machine learning of neuroimaging and multimodal data, and big healthcare data analysis. Applications include cancer, neural disorders, infectious diseases, and digital health.

Dr. Meyer-Baese has an MS degree in electrical and computer engineering and a PhD in computational neuroscience from the Technical University of Darmstadt. She wrote three research monographs in medical imaging and over 300 peer-reviewed papers. Her research interests are in dynamical graph theory and generative AI applied to medical imaging.

Dr. Michael Killian is an associate professor of social work at FSU specializing in pediatric solid organ transplantation. His NIH-funded research uses digital health technologies to study medication adherence and psychosocial risk to improve child and family health outcomes post-transplant. He fosters interdisciplinary collaboration between social work and medicine.

Dr. Zhe is a full professor in the School of Information and Director of the Institute for Successful Longevity at FSU. As a biomedical informatician, his research intersects with biomedical/health informatics, computer science, and information science. He specializes in machine learning, NLP, and knowledge representation. He is an elected fellow of IAHSIand AMIA.

Dr. Gubanov is an assistant professor and a lead PI on a multi-year NSF ($550K) grant and a Casey DeSantis Cancer Innovation Fund ($1.2M) consortium grant with Moffitt Cancer Center to develop new AI for better cancer practices. He earned his PhD from the University of Washington and completed a postdoc at MIT CSAIL. His honors include the Amazon AI AWS Research Award, the Communications of the ACM (CACM) Award, the ACM SIGMOD Research Highlights Award, and the IEEE ICDE Best Paper Award.