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Dr. Mei Liu, Ph.D.

Mei Liu

Associate Professor
Interim Director of Medical Informatics


Mei Liu, Ph.D. is an Associate Professor and Interim Director of Medical Informatics in the Department of Internal Medicine. She received her Ph.D. in Computer Science from the University of Kansas and completed her National Library of Medicine 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 the 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 natural language processing (NLP) and secondary use of EHR data to model patient risks and disease trajectories and discover underlying risk factors.

Research Overview

Dr. Liu's 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 reactions, diabetic kidney disease, acute kidney injury (AKI), and sepsis predictions. She is the Principal Investigator for an 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. She is also the site-PI for KUMC's involvement in the CDC-funded Natural Experiments for Translation in Diabetes 2.0 (NEXT-D2) project led by investigators from Northwestern University that aims to study the effect of Medicaid expansion on diabetes diagnosis and care.

Currently, she co-leads the KU CTSA Frontiers Informatics Core on enhancing the clinical data warehouse HERON and expanding its informatics capabilities. During the COVID-19 pandemic, she has been leading the Medical Informatics team at KUMC in rapidly responding to national data initiatives such as the NCATS National COVID Cohort Collaborative (N3C), the CDC funded PCORnet COVID project, and the Consortium for Clinical Characterization of COVID-19 by EHR (4CE).

Published work can be found in the following links:

Last modified: Jul 22, 2021