Dr. Meyer-Baese’s research interests include medical imaging with a focus on pattern recognition techniques applied to breast MRI, computer-aided diagnosis, fMRI data analysis; computational biology in the dynamic analysis of gene regulatory networks, graph theoretical concepts applied in therapeutics of glioblastoma, stem cells, and phosphoproteomics; and computational neuroscience of brain-based classification techniques, nonlinear stability analysis of cortical systems, and graph theory applied to cortical networks.

Dr. Rodriguez’ research focus Dr. Rodriguez’s research focus is precision preventive medicine, specifically; health education, early diagnosis of medical conditions, and cell-based preventive therapeutics.

Dr. Pritchard has dedicated her efforts to fostering the university’s connection with Mayo Clinic, establishing a comprehensive collaboration agreement across the campus. In her new position, she has been entrusted with the task of broadening FSU’s involvement with Mayo as the university advances FSU Health—an initiative set to revolutionize healthcare provision in North Florida. This initiative encompasses the establishment of the Academic Health Center at the Tallahassee Memorial HealthCare campus and a healthcare campus in Panama City Beach. Pritchard brings valuable expertise in forging and nurturing strategic alliances that bridge the gap between industry and academia, particularly in the realm of health innovation. Before joining FSU, she founded a company specializing in aiding medical technology startups to create and introduce state-of-the-art medical devices, frequently stemming from breakthroughs in university research.

Dr. Jinfeng Zhang completed his Ph.D. in the Department of Engineering at the University of Illinois at Chicago in 2004. Following that, he underwent postdoctoral training in the Department of Statistics at Harvard University from 2004 to 2007. In 2007, Dr. Zhang became a faculty member in the Department of Statistics at Florida State University. His research encompasses applications of computational methods and artificial intelligence in biology, including biological information extraction, biomedical knowledge graphs, and AI for Science.

Dr. Liu’s current research focus is on the development of novel machine learning and artificial intelligence techniques to accelerate risk factor identification and discovery in medicine using EHR data. Clinical applications of her research include adverse drug reaction, diabetic kidney disease, acute kidney injury (AKI), and sepsis predictions. She is the Principal Investigator for a NIDDK R01 project and an NSF Smart and Connected Health project that focus on the identification of personalized risk factors of AKI with personalized modeling and causal learning and building a secure and robust AKI prediction model with privacy-preserving federated transfer learning using EHR data from 11 PCORnet sites across 9 states.

Rickey Carter, PhD is Professor of Biostatistics at Mayo Clinic in Florida. He received his training in biostatistics at the Medical University of South Carolina and has over 20 years of experience with study design and analysis for clinical and translational research. Administratively, he serves as a Vice Chair for the Department of the Quantitative Health Sciences and as the Scientific Director for the Digital Innovation Lab, a machine learning shared resource on Mayo’s Florida campus. Dr. Carter has research interests that span clinical trial optimization to the development of digital biomarkers using machine learning techniques. He is an active collaborator and has over 375 peer reviewed publications.

Dr. Wu’s research interests include natural language processing (NLP), machine learning, computational drug repurposing, and applications of artificial intelligence (AI) technologies to electronic health records for clinical and translational research. He has published over 80 peer-reviewed papers and has been the principal investigator for grants from the National Institutes of Health (NIH) and Patient-Centered Outcomes Research Institute.