Mei Liu

Dr. Liu is an Associate Professor with Tenure in the Department of Health Outcomes and Biomedical Informatics (HOBI), the Director of Predictive Analytics and Associate Director of Graduate Education in HOBI. She also serves as the Associate Director of Biomedical Informatics and Data Science for the Institute for Child Health Policy and the Director of Biomedical Informatics of the University of Florida Clinical and Translational Science Institute (CTSI).

Dr. Liu received her PhD in Computer Science from the University of Kansas and completed her National Library of Medicine (NLM) postdoctoral fellowship in biomedical informatics at Vanderbilt University. Her research interest in bioinformatics began during her doctoral study with the development of novel machine learning algorithms to improve prediction of protein-protein interactions and protein functions. Her research interest expanded to medical informatics while at Vanderbilt with the development of machine learning models to detect and predict adverse drug reactions using electronic health records (EHRs). Her other research interests include the secondary use of EHR data to model patient risks and disease trajectory and discover underlying risk factors.

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 two NIDDK R01 projects 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.