Rate My Professor Jinling Liu

Dr. Liu's research specializes in genetic epidemiology, focusing on developing and applying novel statistical and machine learning methods to model big data from multi-omics sources, including whole genome sequencing, epigenomics, transcriptomics, proteomics, and metabolomics, for precision medicine. Her work addresses genomic causes of diseases such as cancer, Parkinson’s disease, and cardiovascular diseases, inferring signaling pathway activations to advance health equity. She has received a prestigious NIH Career Development Award for young investigators and is Principal Investigator on two active NIH National Heart, Lung, and Blood Institute grants: "A novel framework for estimating personalized genomic variants of hypertension for precision medicine" (September 2023) and "Investigation and deployment of novel Bayesian inference algorithms in CAVATICA for identifying genomic variants underlying congenital heart defects in Down syndrome individuals" (May 2024). Key publications include "A genome-wide association study coupled with machine learning approaches to identify influential demographic and genomic factors underlying Parkinson’s disease" (Frontiers in Genetics, 2023), "An individualized Bayesian method for estimating genomic variants of hypertension" (BMC Genomics, 2023), and "IBI-DT: a novel approach combining individualized Bayesian inference and decision tree for precision medicine" (Briefings in Bioinformatics, 2025). Dr. Liu teaches courses including Genetic Epidemiology and supervises PhD students and postdoctoral fellows.