Dissertation: Statistical Methods for the Analysis of Error-Prone Electronic Health Records: Impact of Source Data Verification, Time Discretized Multiple Imputation, and Variance Estimation with Incompatible Imputation and Analysis Models

Advisor: Bryan Shepherd

MS, Biostatistics, University of Washington; BS, Statistics and Mathematics, University of Missouri-Columbia

At Harvard T. H. Chan School of Public Health since 2018. Currently Research Scientist, Center for Biostatistics in AIDS Research (CBAR).

Dissertation: On False Discovery Rates for Second-Generation p–Values

Advisor: Jeffrey Blume

BS, Mathematics (minor in Biology), Georgia Southern University

Dissertation: Coping With Complexities in High Dimensional Data: PheWAS in EMR and Statistical Inference in fMRI Data

Advisor: Hakmook Kang

BS, Biochemistry, University of Washington

At Genentech since 2020. Currently Statistical Scientist.

Thesis: Conditional Associations with Big Data: Estimating Adjusted Rank Correlations in the Electronic Health Record

Advisor: Bryan Shepherd

PhD, Theoretical Physics, Vanderbilt University; BS, Physics, Harbin Institute

At Amazon since 2017. Currently Senior Research Scientist.

Dissertation: Improving Modern Techniques of Causal Inference: Finite Sample Performance of ATM and ATO Doubly Robust Estimators, Variance Estimation for ATO Estimators, and Contextualized Tipping Point Sensitivity Analyses for Unmeasured Confounding

Advisor: Robert Greevy

MS, Biostatistics, Washington University; BA, Religious Studies and Romance Languages, University of North Carolina

At Wake Forest University since 2019. Currently Associate Professor of Statistical Sciences, Biostatistics and Data Science.

Thesis: Identifying Patterns of Abridged Life Table Elements

Advisor: Robert Johnson

BS, Mathematics, Belmont University

At University of Tennessee since 2020. Currently PhD student, Data Science & Engineering.

Dissertation: Sequential Rematched Randomization and Adaptive Monitoring with the Second-Generation p-Value to increase the efficiency and efficacy of Randomized Clinical Trials

Advisor: Robert Greevy

MS, Biostatistics, University of Minnesota; BS, Statistical Science, Brigham Young University

At University of Utah since 2019. Currently Assistant Professor of Biostatistics.

Thesis: Using Statistical Learning Methods for Better Spectrum Classification

Advisor: Ming Li

BS, Biological Sciences and Biotechnology, Tsinghua University

At Meta since 2022. Currently Senior Machine Learning Engineer.

College: Middle Tennessee State University

Mentor: Bryan Blette

Project: A Machine Learning Tool for Imputation of Body Fat Percentage

College: Middle Tennessee State University

Mentors: Bryan Shepherd and Gustavo Amorim, with Joshua Slone

Project: Statistical Analysis and Design for International Study of HIV/AIDS