Hi! This is Nan. My research focuses on developing scalable statistical machine learning methods to detect key signals and reveal meaningful patterns from high-dimensional data. My Erdős number is 4.

My industry experience dedicates to designing and implementing cloud-based data analysis solutions for leading pharmaceutical & life science research organizations. By connecting the dots in data science and product engineering, my core mission is to make genomic data analysis collaborative and reproducible.

I am an active contributor to the R community, with 20+ open source R packages and Shiny applications for machine learning, data visualization, and reproducible research. I won the 2018 John M. Chambers Statistical Software Award from the American Statistical Association for my R package liftr.