Research

My research interests are probability and statistical theory and computational statistics for new technology-generated multi-domain data.

My current applied research is probabilistic modeling for microbiome genome-level data and host immune response in pregnant women to elucidate interactions.

My current theoretical research focuses on approximation theory for learning dependency in high-dimensional data.

Statistical Methods for Multi-domain Data

Multi-table statistical methods

Statistical Methods for Microbiome Data

Statistical Methods for 16S and shotgun metagenomics data.

Microbiome Studies

Analyzing microbiome genome-level data and reproducible research.

Approximation theory in statistics

Saddlepoint-based bootstrap method (SPBB), multivariate SPBB, extension of empirical saddlepoint approximation for right-censored data, bivariate saddlepoint approximations.