Current Fellows in the Biostatistics Branch

Dr. Agarwala, postdoctoral fellow in BB, is working on projects related to an estimation problem for survival data with special features and the combination of high-dimensional biomarkers to assess prevalence of infection with SARS- CoV-2, under the mentorship of Ruth Pfeiffer, Ph.D.

Dr. Anyaso-Samuel, postdoctoral fellow in BB, develops efficient statistical and computational methods for longitudinal microbiome data, spatial heterogeneity of tumors and biological networks. His mentors are Dr. Jianxin Shi and Dr. Paul Albert.

Mr. Aron, predoctoral fellow in BB, develops hidden Markov models for characterizing the heterogeneity of the wake cycle. His mentor is Paul Albert, Ph.D.

Dr. Étiévant, postdoctoral fellow in BB, began developing statistical methods for causal inference in longitudinal datasets and methods for high-dimensional mediation analysis prior to coming to DCEG. She continues working in these areas and on inference for HPV vaccine trials under the mentorship of Mitchell H. Gail, M.D., Ph.D.

Ms. Hill is pursuing her B.S. in statistics from the University of Maryland, Baltimore County. She will conduct research in DCEG as part of a scholarship from the National Institute on Drug Abuse. Ms. Hill is working on cancer risk analyses using imperfect cancer registry linkage data under the mentorship of Danping Liu, Ph.D., investigator.

Dr. Hua, postdoctoral fellow in BB, is working on developing novel statistical methods for mutational signatures extractions and their contributions to somatic mutations in cancer genomes, under the mentorship of Bin Zhu, Ph.D.

Sang Kyu Lee, predoctoral fellow in BB, is working on quantile regression and survival analysis for high-dimensional data, especially about false discovery rate (FDR) control on variable selection and disparity analysis with cancer-related biomarkers, under the mentorship of Hyokyoung (Grace) Hong, Ph.D.

Dr. Mao, postdoctoral fellow in BB, 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, under the mentorship of Li Cheung, Ph.D.

Dr. Miranda-Filho, postdoctoral fellow in the Biostatistics Branch (BB), is conducting research in the field of descriptive cancer epidemiology by applying statistical and mathematical models to elucidate emerging trends in cancer incidence, mortality, and survivorship among world populations. He also serves as an affiliate in the Integrative Tumor Epidemiology Branch (ITEB). His mentors are Philip Rosenberg, Ph.D., BB, and Gretchen Gierach, Ph.D., M.P.H., ITEB.

Dr. Roberti, postdoctoral fellow in REB and BB, investigates statistical methods as applied to studies of radiation, in particular related to the Chernobyl nuclear reactor accident. His mentors are Elizabeth Cahoon, Ph.D., and Li Cheung, Ph.D.

Dr. Roy, postdoctoral fellow in BB, is developing methods for identifying longitudinal biomarkers for time-to-cancer outcomes in high-dimensional settings.

Dr. Williams, postdoctoral fellow in BB, conducts his research to improve the accuracy of polygenic risk scores (PRSs) by creating a method to combine PRSs from rare genomic variants with those from common genomic variants. His mentor is Haoyu Zhang, Earl Stadtman investigator.

Dr. Qin, postdoctoral fellow in BB, is working on statistical genetics and genomics, particularly, the integration analysis of single cell sequencing data and GWAS data, detection of copy number variants, and identification of spatially variable genes with single-cell sequencing data, under the mentorship of Dr. Kai Yu and Dr. Jianxin Shi.

Ms. Zhang, predoctoral fellow in BB, is developing mixed modeling approaches to examine the relationship between high-dimensional biomarker/genomics data and subsequent cancer risk, under the mentorship of Dr. Grace Hong and Dr. Paul Albert.