Boran Gao

Boran Gao

Assistant Professor in Statistics

About

Hi! I’m Boran Gao, a tenure-track assistant professor in the Departments of Statistics and Biological Sciences at Purdue University. I earned my Ph.D. in Biostatistics from the University of Michigan, Ann Arbor, under the supervision of Xiang Zhou. I have a broad interest in statistical genetics and genomics including, GWAS, heritability/genetic correlation estimation, mendelian randomization, and fine-mapping, integrating GWAS and spatial transcriptomics.

My work and research

My research interests focus on developing statistical methods and computational tools to address pivotal biological questions emerging from large scale and high-dimensional data, such as biobank level genome-wide association studies (GWASs) and various functional genomic data, including transcriptomics and proteomics. Most of these data predominantly feature European populations, leaving non-European populations underrepresented. In response to this disparity, a particular emphasis of my work is on underrepresented populations. I am devoted to advancing the genetic understanding of complex traits through the development of statistical methods and computational tools that are inclusive of multiple ancestries. Through this approach, my goal is to not only address the broad biological questions that emerge from expansive data but also to bridge the gap in genetic research, fostering inclusivity and equity in scientific discovery.

In particular, the methodological aspects of my past and current work center on three areas: (1) developing efficient and powerful statistical methods to unravel the shared genetic basis across diverse traits and ancestries in GWASs. (2) developing a powerful and scalable statistical method for multi-ancestry fine-mapping. (3) developing a powerful and scalable statistical method for multi-ancestry colocalization that integrates GWASs with bulk RNA-seq. Moving forward, I envision my research endeavors developing statistical methods motivated by significant challenges in GWAS and multi-omics data, with a particular focus on underrepresented populations.

I work in the field of statistical genetics, mainly developing statistical tools for GWAS studies. I have experience in developing models for genetic correlation estimation, mendelian randomization, colocalization and fine-mapping. For the detailed research description and tools developed, please visit.

My background

I received my M.S. in Biostatistics from the University of Michigan, School of Public Health, my MPH in Epidemiology from the University of Michigan, School of Public Health, and my MBBS in Soochow University.

Selected Awards

  • Rackham One-Term Dissertation Fellowship, University of Michigan 2023

  • Excellence in Research Award, Department of Biostatistics, University of Michigan 2023

  • Charles J. Epstein Trainee Award, Predoctoral Semifinalist, ASHG 2022

  • Rackham Travel Award, University of Michigan 2022

  • Outstanding GSI, Department of Biostatistics, University of Michigan 2017

Open Positions:

Applications are invited for postdoctoral fellow positions in my research group. The successful candidates will be working on various research topics in developing statistical methods and computational tools for genetics and genomics data. The candidate should hold a Ph.D. in biostatistics, statistics, computer science, bioinformatics, computational biology, mathematics, or related quantitative discipline. Please send me a CV, a short statement of research interests, and contact information of three referees to: Boran Gao gao824@purdue.edu. Review of applications will begin immediately and continue until the position is filled.