Current Fellows in the Biostatistics Branch

Dr. Anyaso-Samuel develops statistical methods for the analysis of microbiome data and biological networks.

Sumaja Bandreddi works on semi-continuous analyses of data from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial.

Dr. Chávez, postdoctoral fellow in BB, develops mathematical and computational methods for mutational signature analysis.

Dr. Kebede applyies novel machine learning methods to characterize and forecast physical activity patterns and forecast in unique populations.

Dr. Mao develops novel statistical methods for the analysis of multistate time-to-event data and the design of cost-effective biomarker studies, with an aim of advancing understanding of cancer etiology and complex cancer processes.

Dr. Qin develops statistical analysis methods for single cell sequencing data, including integration analysis with GWAS data, copy number estimation and spatially variable gene identification.

Dr. Roberti investigates statistical methods as applied to studies of radiation, in particular related to the Chornobyl nuclear reactor accident.

Dr. Roy develops methods for identifying longitudinal biomarkers data for time-to-cancer outcomes in high-dimensional settings.

Dr. Williams conducts research with the goal of creating a method to obtain polygenic risk scores from rare genomic variants and combine them with polygenic risk scores from common genomic variants to ultimately increase accuracy.

Dr. Veith studies tumor evolution and complex genomic features through whole-genome sequencing–based studies.

Dr. Zhang develops mixed modeling approaches to examine the relationship between high-dimensional biomarker/genomics data and subsequent cancer risk.