Summary
Zitao Zhang is a biostatistics researcher and data scientist with eight years of cross-disciplinary experience applying statistical modeling, machine learning, and high-performance computing to genomics and clinical trials. Currently a Research Assistant at Columbia Mailman, he specializes in single-cell RNA-seq analysis—using Seurat and LAMIAN—to reconstruct cellular trajectories and uncover dynamic gene expression linked to hematopoiesis and leukemia. His background spans industry and academia, from building MMRM analyses and R Shiny dashboards for a Phase 3 clinical trial at Bristol Myers Squibb to developing knockoff-based feature selection with deep VAE architectures at Memorial Sloan Kettering. Comfortable in R, Python, SQL, Rust, Go, and Ruby, Zitao blends rigorous Bayesian inference with practical pipeline engineering to make large-scale transcriptomic analyses reproducible and interpretable. He is drawn to precision medicine applications and often bridges computational method development with translational oncology teams to accelerate biomarker discovery.
8 years of coding experience
1 year of employment as a software developer
Undergraduate, Statistics: Data Science, Undergraduate, Statistics: Data Science at University of Washington
Master of Science - MS, Biostatistics, Master of Science - MS, Biostatistics at Columbia University Mailman School of Public Health