Current Fellows in the Biostatistics Branch
Meet the fellows in the Biostatistics Branch (BB) and learn about their work.
Meet the fellows in the Biostatistics Branch (BB) and learn about their work.
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Samuel (Sam) Anyaso-Samuel, Ph.D., Postdoctoral FellowDr. Anyaso-Samuel develops statistical methods for the analysis of microbiome data and biological networks.
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Jordan Aron, B.A., Predoctoral FellowMr. Aron develops hidden Markov models for characterizing the heterogeneity of the wake cycle
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Liana Hill, Prebaccalaureate FellowMs. Hill is working on cancer risk analyses using imperfect cancer registry linkage data under the mentorship of Danping Liu, Ph.D., investigator.
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Min Hua, Ph.D.Dr. Hua works on developing novel statistical methods for mutational signatures extractions and their contributions to somatic mutations in cancer genomes.
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Sang Kyu Lee, M.S., Predoctoral FellowMr. Lee 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.
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Fangya Mao, Ph.D., Postdoctoral FellowDr. 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.
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Fei Qin, Ph.D., Postdoctoral FellowDr. Qin develops statistical analysis methods for single cell sequencing data, including integration analysis with GWAS data, copy number estimation and spatially variable gene identification.
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Sander Roberti, Ph.D., Postdoctoral FellowDr. Roberti investigates statistical methods as applied to studies of radiation, in particular related to the Chornobyl nuclear reactor accident.
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Siddharth Roy, Ph.D.Dr. Roy develops methods for identifying longitudinal biomarkers data for time-to-cancer outcomes in high-dimensional settings.
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Jacob Williams, Ph.D.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.
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Joycelyn Williams, B.S.Ms. Williams is exploring somatic LINE1 retrotransposon insertions in blood as potential cancer biomarkers.
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Pei Zhang, M.S.Ms. Zhang develops mixed modeling approaches to examine the relationship between high-dimensional biomarker/genomics data and subsequent cancer risk.
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Kehao Zhu, Ph.D.Dr. Zhu studies statistical methodologies related to cancer biomarkers and cancer screening trials.