My research focuses on developing and applying statistical and computational methods for large-scale biomedical and epidemiologic studies. I am particularly interested in integrating genomic, transcriptomic, microbiome, spatial, and clinical data to better understand disease risk, biological mechanisms, and disease progression.

Current areas of interest include cancer genomics and genetic epidemiology, microbiome epidemiology, integrative multi-omics analysis, and network-based modeling of molecular data. Methodologically, my work draws on graphical models, high-dimensional inference, cluster-correlated data analysis, and survival and multistate methods.

My long-term goal is to develop computationally efficient and statistically rigorous methods that enable reproducible analysis of complex biomedical data and translate high-dimensional molecular information into insights relevant to cancer prevention, epidemiology, and clinical research.

Training and Appointments

2026–present
Assistant Professor, Department of Epidemiology and Biostatistics
University of South Carolina

2023–2026
Postdoctoral Fellow, Division of Cancer Epidemiology & Genetics, National Cancer Institute
Mentors: Jianxin Shi and Paul Albert

2019-2023
Ph.D. in Biostatistics, University of Florida
Advisor: Somnath Datta

2017-2019
M.S. in Mathematics, Boise State University
Advisor: Partha Mukherjee