Hi there! This is Nan.

My research focuses on developing scalable statistical machine learning methods to detect key signals and reveal meaningful patterns from high-dimensional biological/chemical/financial data. My current Erdős number is 4.

I build open source software for statistical learning, data visualization, and computational reproducibility. My most popular R packages include msaenet, ggsci, protr, and liftr (John M. Chambers Statistical Software Award, 2018).

My industry experience dedicates to building tailored, cloud-based solutions for the most challenging computational problems in genomics and precision medicine. By connecting the dots in data science and product engineering, my mission is to make drug discovery faster, cheaper, collaborative, and reproducible.