I am a statistician from Merck & Co. I work in the Methodology Research group led by Keaven M. Anderson in BARDS. My focus is at the intersection of statistical methodology research and software architecture innovation.

My research interests include sparse linear models, representation learning, and computational reproducibility. I build software in R to automate my workflow. My favorites include msaenet, oneclust, liftr, ggsci, and pkglite.

Previously, I worked as a data scientist at Seven Bridges in Boston. Earlier in my career, I studied human genetics in Matthew Stephens Lab at the University of Chicago. I earned my PhD degree in statistics from Central South University, China. My thesis focused on developing statistical learning methods for high-dimensional data analysis, advised by Qing-Song Xu.