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. Dill, postdoctoral fellow in BB, examines the effect of quitting smoking on the relative and absolute risk of smoking-related cancers, and also estimates incidence rates of second primary lung cancer in individuals with prior history of cancer, under the mentorship of Hormuzd A. Katki, 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.

Dr. Fu, postdoctoral fellow in BB, works with Kai Yu, Ph.D., on developing new procedures for statistical inference and building prediction models with high-dimensional genetic and genomic data, and with Haoyu Zhang, Ph.D., on developing methods for testing genetic associations while accounting for cancer subtype heterogeneity.

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. Ramos, postdoctoral fellow in BB, applies multiple testing methods to studies in metabolomics and lipidomics and liver cancer and applies his experience in sampling theory to statistical methods for designing and analyzing novel epidemiologic designs when invasive biospecimens can only be collected on subsamples of a cohort. He works under the mentorship of Dr. Barry Graubard and Dr. Hormuzd Katki.

Mr. Roy, predoctoral fellow in BB, is working on his Ph.D. dissertation under the NIH Graduate Partnership Program with his BB mentors Danping Liu, Ph.D., and Paul Albert, Ph.D., and his UMBC advisor Dr. Anindya Roy. He is developing statistical models for analyzing longitudinal biomarker data for cervical precancer prediction.

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.

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.