Analytical/Research Staff

  • Onika Abrams

    Research Data Specialist

    MSPH, Applied Epidemiology, University of Alabama at Birmingham

     

  • Aihua Bian

    Principal Biostatistician

    MPH, University of Texas Southwestern

    Research interests include: time-to-event analysis, clinical trials, competing risk event analysis, categorical data analysis, repeated measurements analysis, observational studies

  • Heather Bickham

    Project Manager

    MPH, Health Behavior and Community Health, New York Medical College

     

  • Caroline Birdrow

    Senior Biostatistician

    MS, Biostatistics, Vanderbilt University

    Primary collaboration: the Critical Illness, Brain Dysfunction, and Survivorship (CIBS) Center

    Research interests include: causal inference, semiparametric g-computation, observational longitudinal data analysis

     

     

     

  • Hua-Chang Chen

    Data Scientist Assistant I

    PhD, Genetics, Shanghai Institute of Plant Physiology and Ecology

    Hua-Chang Chen focuses mainly on inferring the underlying causal genes for severe diseases by utilizing GWAS (Genome-Wide Association Study) and Mendelian randomization. His work also includes predicting risk genes/domains by integrating multi-omics data.

     

  • Josh DeClercq

    Principal Biostatistician

    MS, Biostatistics, Vanderbilt University

    Primary collaborations include: Vanderbilt Specialty Pharmacy; Department of Physical Medicine and Rehabilitation; Center for Research and Innovation in Systems Safety

    Current projects include: developing a standard measure of medication adherence and a clinical trial for rotator cuff tear treatment

    Winner of the 2020 Linda Stewart Applied Analysis Report Award, presented annually to recognize an exceptional applied analysis report written by a staff biostatistician, for "Healthcare Costs and Utilization Project."

  • Tan Ding

    Senior Biostatistician

    MS, Statistics, University of Georgia

    Research interests include: time-to-event analysis, mixed-effects modeling, categorical data, power analysis, sample size calculation

  • Andrea Elhajj

    Research Data Specialist

    MS, Civil and Environmental Engineering (Data Science Concentration), University of Vermont

  • Run Fan

    Principal Biostatistician

    PhD, Microbiology, University of Alabama at Birmingham

    MS, Biostatistics, Vanderbilt University

    Winner of the 2017 Linda Stewart Applied Analysis Report Award, presented annually in recognition of an exceptional statistical analysis report written by a staff biostatistician

    Data analyst for the ARC (Arthroscopic Rotator Cuff) Trial, Shoulder Study Research Group

  • Xiaoke (Sarah) Feng

    Senior Biostatistician

    MS, Statistics, University of Texas at Dallas

    MS, Mathematics, University of New Orleans

    Primary collaboration: Department of Anesthesiology

    Research focus/interests:  longitudinal data analysis, survival data analysis, categorical data, statistical analysis with missing data, mixed effects models

  • Yue Gao

    Senior Biostatistician

    MS, Biostatistics, Vanderbilt University

    MEd, Quantitative Methods, Vanderbilt University

    Research interests include: clinical trials, health services research, and longitudinal and survival analysis

     

  • Nicolas Gargurevich

    Biostatistician

    MS, Biostatistics, University of Michigan

    Research interests include: clinical trials, mental health research, and public health studies pertaining to nutrition, infectious disease, and sexual and reproductive health

  • Andrew Guide

    Senior Biostatistician

    MS, Biostatistics, University of Michigan

    Research interests include: heart and kidney disease

     

     

  • Bryan Helm

    Senior Statistical Genetic Analyst

    PhD, Ecology and Evolutionary Biology, University of Arizona

    Research interests include: rare pediatric cancers (germline predisposition, biomarkers, precision medicine), bioinformatics, genomics, transcriptomics, advanced data analysis, data science, R

     

     

  • Brant Imhoff

    Senior Biostatistician

    MS, Statistics, Miami University (Oxford, Ohio)

     

    Primary collaborations: Pragmatic Critical Care Research Group, heart failure, emergency medicine


    Research interests include: non-parametric statistics, machine learning, time series analysis, predictive modeling, clinical trials

  • Rebecca Irlmeier

    Senior Biostatistician

    MS, Biostatistics, Vanderbilt University

    Research interests include: continuous quality improvement in healthcare; clinical prediction models and real-time implementation to improve patient outcomes; omics research, including high-dimensional genotyping, transcriptomic, and proteomic data; deep phenotyping data; design and analysis of clinical trials; survival analysis; longitudinal analysis; machine learning and artificial intelligence

  • Amir Javid

    Biostatistician

    MS, Statistics, Oklahoma State University • PhD, Civil Engineering, Oklahoma State University

    Research experience includes: flood detection and monitoring, tree failure detection, drought monitoring with machine learning models

  • Cathy Jenkins

    Lead Biostatistician

    MS, Biostatistics, University of North Carolina

    Winner of the 2014 Linda Stewart Applied Analysis Report Award, presented annually in recognition of an exceptional statistical analysis report written by a staff biostatistician

  • Lauren E. King

    Senior Project Manager

    MPH (Epidemiology Concentration), University of Alabama at Birmingham

  • Jess Lai

    Lead Program Manager

    Research programs include: ACTIV-6, CODA, IVY-4, IVY-5, and various cross-departmental and multi-site data coordinating center projects, such as the VBDCC

  • Aaron Lee

    Senior Biostatistician

    MS, Biostatistics, Vanderbilt University

  • Yajing Li

    Senior Biostatistician

    MS, Biostatistics, University of Michigan

  • Yunqi "Vicky" Liao

    Biostatistician

    MS, Biostatistics (Epidemiology minor), University of Texas Health Science Center at Houston

    Research interests include: cancer-related research, EHR data, categorical data analysis, observational studies, data management

  • Cara Lwin

    Biostatistician

    MS, Biostatistics, Vanderbilt University

     

     

  • Trey McGonigle

    Biostatistician

    MS, Statistics, University of California, Riverside

    Winner of the 2022 Linda Stewart Analysis Report Award.

     

  • Ryan Moore

    Senior Biostatistician

    MS, Biostatistics, Vanderbilt University

    Primary collaborations: Vanderbilt Specialty Pharmacy; Advanced Artificial Intelligence Laboratory (AVAIL). Co-investigator, "Predicting risk of systemic autoimmune disease in patients with positive antinuclear antibodies" (PI: April Barnado)

    Winner of the 2021 Linda Stewart Applied Analysis Report Award, presented annually in recognition of an exceptional statistical analysis report written by a staff biostatistician, for "Patient-centered services to improve specialty medication adherence: A randomized clinical trial"

    Organizer of the department's Statistical Computing Series

  • Samuel Nwosu

    Lead Biostatistician

    MS, Biostatistics, Middle Tennessee State University

  • Onur Orun

    Principal Biostatistician

    MS, Statistics, Colorado State University

    MS, Mathematics, Bilkent University, Turkey

    Primary collaboration: The Critical Illness, Brain Dysfunction, and Survivorship (CIBS) Center

    Winner of the 2019 Linda Stewart Applied Analysis Report Award, presented annually in recognition of an exceptional statistical analysis report written by a staff biostatistician, for "Vitamin D to Improve Outcomes by Leveraging Early Treatment: Long-term Brain Outcomes in Vitamin D Deficient Patients (VIOLET-BUD)"

    Winner of the 2023 Linda Stewart Applied Analysis Report Award for "BRAIN-ICU Long-term Outcomes Latent Trajectory Analysis Report"

  • Amy Perkins

    Lead Biostatistician

    MS, Biostatistics, University of Pittsburgh

  • Marisol Ramirez-Solano

    Principal Statistical Genetic Analyst, Department of Biostatistics
    Core Facility Manager and Senior Bioinformatics Analyst, VANGARD

    MS, Biochemistry, Universidad Nacional Autónoma de México

    Research interests include: small RNA sequencing and single-cell sequencing data

  • Paridhi Ranadive

    Biostatistician

    MS, Biostatistics, University of North Carolina

    Skills and certifications include: categorical, longitudinal data, and survival analysis; sample size and power calculation; OLS, GLM and web scraping; machine learning; signal and image processing

    Research interests include: imaging, air pollution, epidemiology

     

     

  • Yaping Shi

    Lead Biostatistician

    MS, Statistics, University of Iowa

    Research interests include: prediction modeling, categorical data, mixed effects modeling, time-to-event data, repeated measures, longitudinal data.

     

  • In Hae (Ine) Sohn

    Biostatistician

    MS, Statistics, North Carolina State University

    Collaborations include: Respiratory Virus Transmission Network (RVTN), Influenza and Other Viruses in the Acutely Ill (IVY-4)

    Research interests include: clinical trials, longitudinal data analysis, data management

  • Joey Stolze

    Senior Statistical Genetic Analyst

    PhD, Genetics, University of Arizona

  • Tess Stopczynski

    Senior Biostatistician

    MS, Statistics, University of Vermont

    Research interests include: infectious diseases, survival analysis, categorical data analysis, trials design

    Areas of collaboration: pediatric infectious diseases, neonatology, hematology

     

  • Mackenzie Stuenkel

    Research Data Specialist

    PhD, Applied Health Research and Evaluation, Clemson University

  • Lili Sun

    Senior Biostatistician

    MS, Biostatistics, Middle Tennessee State University

    PhD, Crop Science, Zhejiang University

    Research interests include: cancer immunotherapy, clinical endpoint, drug development

  • Yunyi Sun

    Biostatistician

    MEd, Quantitative Methods, Vanderbilt University 

    Research interests: non-parametric method, bootstrapping technique, Bayesian statistics, applied regression, machine learning, principal component analysis, multivariate statistics, clustering analysis

    Primary collaboration: Alzheimer's disease

  • (Sydney) Afan Swan

    Senior Research Data Specialist

    MPH, Epidemiology, University of Alabama at Birmingham

    Primary collaboration: IVY-4 (Influenza and Other Viruses in the Acutely Ill)

    Research interests include: epidemiology, molecular biology, and bacteriology

     

  • Guanchao Wang

    Biostatistician

    MS, Biostatistics, University of Minnesota

    Research interests include: Bayesian approaches to meta-analysis

  • Li Wang

    Lead Biostatistician

    MS, Statistics and Biological Engineering, University of Georgia

    Primary collaboration: Vanderbilt Institute for Clinical and Translational Research (VICTR).

    Research interests include: clinical prediction models, pragmatic clinical trials, statistical computing, mixed-effects models, time-to-event analysis

  • Yu Wang

    Staff Scientist

    PhD, Crop Science (Bioinformatics branch), Zhejiang University

    Research interests include: bioinformatics, population genetics, molecular evolution, non-coding small RNAs, translation informatics, immunotherapy in cancer.

  • Ke Xu

    Biostatistician

    MS, Biostatistics and Biomedical Informatics, University of Florida

    Researchinterests include: omics, fMRI imaging data

    For more information: xkcococo.github.io

  • Meng Xu

    Lead Biostatistician

    MS, Statistics, University of Idaho

     

  • Elisa Yazdani

    Biostatistician

    MS, Biostatistics, Vanderbilt University 

    Research interests include: pharmacokinetics, electrophysiology, cognitive disorders, clinical trials

  • Zhihong Yu

    Senior Biostatistician

    MS, Applied Statistics, Purdue University

    PhD, Chemical Biology, Nankai University (China)

    Research interests include: generalized linear models; mixed effects modeling; longitudinal data analysis; categorical data analysis; time-to-event data analysis; computer-assisted drug discovery