Dr. Liu completed doctoral training in pattern recognition and artificial intelligence, with strong expertise in natural language processing, machine learning (deep learning), and biomedical informatics. He is currently an Associate Professor in Health Informatics and the founding director of the innovative AI for Health (iAI4Health) lab. He was awarded as an NIH AIM-AHEAD leadership fellow in 2022 and has been selected to serve as a scientific advisor for NIH All of US research scholar program and NIH AIM-AHEAD leadership fellowship program since 2023. His research focuses on exploiting advanced computational models to analyze heterogeneous and complex healthcare data for knowledge extraction, predictive modeling and preventative data analytics, in the areas of suicide risk prediction, HIV prevention, cancer informatics, and cardiometabolic disease management.   

Dr. Liu has published more than 70 peer-reviewed manuscripts (over 30 first-author) on premium journals and top computer science conferences. His research has been continuously funded by NIH as PI, MPI, or leading data scientists. Dr. Liu participated in NSF and NIH study sections in the areas of machine learning, natural language processing, and clinical predictive modeling. Through developing advanced machine learning methods, Dr. Liu has won first place in two international challenge tasks: Medical Visual Question Answering (2018) and Gene Mutation/Disease Relation Extraction (2019).

Recently, Dr. Liu's research has focused on applying AI techniques to advance health equity, assessing and mitigating potential biases related to data processing and algorithmic training.