Buu’s primary research focuses on developing and applying statistical methods for exploration of genetic architecture and genomic studies such as genome-wide association study (GWAS), polygenic risk scores (PRS), gene-by-environment analysis, RNA-Seq, and single-cell RNA-Seq analysis. He is also interested in machine learning, causal inference algorithms for multi-omics data.
 
My website: https://buutrg.github.io/

Awards/Honors:
Harvard T.H. Chan School of Public Health, Department of Epidemiology’s Excellence in Teaching Award for 2026!

Prior to joining HSPH, I completed my undergraduate studies at Vanderbilt University, where I majored in Mathematics and Economics. I joined the Liang Lab in August 2023 and have been focusing on genetic data analysis and predictive polygenetic models. Additionally, I have a keen interest in natural language processing (NLP) and other machine learning techniques