My research interests include methodological development in omics data modeling and collaborating with biomedical scientist to elucidate biological mechanisms of complex disease systems and develop new drugs.

Currently, the advancement in high throughput technologies is revolutionizing the fields of biomedical research, giving rise to large-scale omics datasets collected from real patients, including high-resolution single-cell and spatially resolved multi-omics data that could help us disentangle the heterogeneity and gain mechanistic understanding of the disease microenvironment, and large cohorts of static or longitudinal multi-omics data with comprehensive clinical information that could help us build predictive models to characterize disease progression and biological characteristics such as cancer metastasis or drug resistance mechanisms.

Most of my current and long-term research goal is to design a suite of interpretable statistical and machine learning tools for modeling complex omics data types. This goal is methodology-driven and biological hypothesis-driven.