Analytical/Research Staff

MSPH, Applied Epidemiology, University of Alabama at Birmingham

MS, Biostatistics (Health Data Science Concentration), University of Michigan

Research experience includes: RNA-seq, longitudinal analysis, anti-anxiety treatment

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

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

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

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.

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."

MS, Statistics, University of Georgia

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

MS, Applied Statistics, Purdue University

Primary Collaborations: Department of Quality, Safety, and Risk Prevention, Center for Patient and Professional Advocacy

Research interests and expertise: pragmatic clinical trials, real-time predictive modeling using EHR data, machine learning and artificial intelligence, continuous quality improvement

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

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

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

MS, Biostatistics, Vanderbilt University

MEd, Quantitative Methods, Vanderbilt University

Research interests include: statistical genetics, clinical trials, infectious diseases

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

MS, Biostatistics, University of Michigan

Research interests include: heart and kidney disease

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

MS, Biostatistics, Vanderbilt University

Primary collaborations include projects with anesthesiology and the COVID-19 and Cancer Consortium

MS, Statistics, Miami University (Oxford, Ohio)

Research interests include: sports science, time series analysis

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

For more information: biostat.app.vumc.org/RebeccaIrlmeier

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

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

MS, Biostatistics, Vanderbilt University

Primary collaborations: Eye Institute; Department of Biomedical Informatics

MS, Biostatistics, University of Minnesota

MPH (Epidemiology Concentration), University of Alabama at Birmingham

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

MS, Biostatistics, Vanderbilt University

MS, Biostatistics, University of Michigan

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

Advisor: Dandan Liu

BS, Microbiology (minors in Chemistry, Computer Science, Neuroscience, and Economics), University of Pittsburgh

MS, Statistics, University of California, Riverside

Winner of the 2022 Linda Stewart Analysis Report Award.

MS, Biostatistics, Vanderbilt University

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

MS, Biostatistics, Middle Tennessee State University

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)"

MS, Biostatistics, University of Pittsburgh

MPH, Epidemiology, Texas A&M University

MS, Biochemistry, Universidad Nacional Autónoma de México

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

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

MS, Biostatistics, Vanderbilt University

MS, Statistics, University of Iowa

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

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

PhD, Genetics, University of Arizona

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

PhD, Applied Health Research and Evaluation, Clemson University

MS, Biostatistics, Middle Tennessee State University

PhD, Crop Science, Zhejiang University

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

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

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

MS, Biostatistics, University of Minnesota

Research interests include: Bayesian approaches to meta-analysis

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

PhD, Crop Science (Bioinformatics branch), Zhejiang University

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

MS, Biostatistics and Biomedical Informatics, University of Florida

Researchinterests include: omics, fMRI imaging data

For more information: xkcococo.github.io

MS, Statistics, University of Idaho

MS, Biostatistics, Vanderbilt University 

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

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