Analyzing Longitudinal Growth Using Mixed-Effects Models
Investigated growth trajectories in a seven-week strength training study across three treatment groups: weights-increasing, repetitions-increasing, and control. Applied random intercept and slope models in R to analyze linear and quadratic trends in strength improvement. Selected AR(1) covariance structure through comparisons of Unstructured, Compound Symmetry, and Toeplitz models using AIC, BIC, and likelihood ratio tests. Identified significant group-specific trends and visualized results to provide actionable insights.
Spatiotemporal Modeling of Air Quality and Disease Cases
Examined the spatiotemporal association between air quality (PM10 levels) and an infectious disease case across Arizona counties from 2000 to 2022. Implemented Moran's I for spatial autocorrelation, ARIMA and SARIMA models for seasonal patterns, and Bayesian spatiotemporal modeling with Integrated Nested Laplace Approximation (INLA). Identified spatial heterogeneity, temporal trends, and seasonality, providing insights into environmental factors influencing disease spread. Leveraged R for data analysis, visualization, and predictive modeling.
Clinical Trial Analysis of Anti-Epileptic Drug Efficacy
Assessed the efficacy of Progabide in a placebo-controlled, double-blinded trial involving 59 participants. Modeled seizure count reductions over time using Generalized Estimating Equations (GEE) with an AR(1) covariance structure. Conducted hypothesis testing in SAS and interpreted results to provide evidence of treatment efficacy.
Bacterial Population Dynamics Under Simulated Microgravity
Analyzed population dynamics and interspecies interactions of Ralstonia and Sphingomonas in a 100-day mixed-culture study under simulated microgravity and standard gravity. Modeled temporal changes in colony size distribution using linear mixed-effects models in R. Investigated species-specific growth patterns and their environmental interactions, providing insights into microbial behavior under spaceflight conditions.
Gender Bias and Educational Opportunity Cost Analysis (Regression Modeling)
Conducted a comprehensive analysis of wage disparities among programmers and engineers in Silicon Valley using the 2000 U.S. Census data. Developed and refined linear regression models to evaluate the effects of gender and educational attainment on income. Explored the economic trade-offs of pursuing higher education degrees, leveraging R for statistical modeling, data visualization, and diagnostics.
Bioinformatics Analysis of the Astronaut Salivary Microbiome (Team Work)
Analyzed the salivary microbiome of astronauts at three time points—pre-flight, during-flight, and post-flight—using 16S rRNA sequencing data. Performed differential abundance analysis, beta diversity analysis (Weighted-UniFrac), and alpha diversity analysis (Shannon Index) to investigate the impact of spaceflight on microbial communities. Identified microbial families potentially associated with mental health stressors using QIIME2 and Python. Results provided preliminary insights into spaceflight-induced microbiome changes and their implications for astronaut health.
Statistical & Quantitative Methods
Linear & generalized linear models (GLM)
Linear & generalized mixed-effects models (LMM / GLMM) for longitudinal and repeated-measures data, including image-derived quantitative outcomes with nested and hierarchical experimental designs
Marginal models (GEE)
Longitudinal & repeated-measures analysis
Bayesian modeling (applied, including nonparametric approaches)
Regression, hypothesis testing, model diagnostics, selection, validation, and interpretation
Data Acquisition, Management & Reproducibility
Large-scale data acquisition and integration from heterogeneous sources, including NOAA, EPA, AZ weather stations (2000-2025), and spaceflight biological experiments
Structured acquisition of confocal fluorescence imaging data from longitudinal, repeated-measures spaceflight and ground-control experiments across multiple time points, material surfaces, and treatment conditions
Automated data cleaning, harmonization, and longitudinal dataset construction using scripted R and Python workflows
Extraction of quantitative measurements from raw .tif image files using batch-processing pipelines (Python: os, shutil, OpenCV, NumPy, pandas)
Data quality control including background thresholding, technical replicate handling, and hierarchical data structuring
Integration of multi-source environmental, temporal, experimental, and image-derived data for downstream statistical modeling
Data quality control, validation, filtering, and reproducible preprocessing pipelines
Reproducible analysis pipelines with documentation, version control, and standardized preprocessing
Exploratory data analysis and visualization using ggplot2, tidyverse
Core Biostatistical & Scientific Expertise
Quantitative study design and statistical analysis planning, including sample size and power considerations
Application of longitudinal, mixed-effects, and marginal modeling frameworks to complex biological and experimental data
Biostatistical consulting and interdisciplinary scientific collaboration with experimental and computational researchers
Statistical support for manuscripts, grant applications, and technical reports
IRB and IACUC statistical review support for human and animal research protocols
Development of reproducible statistical workflows and cross-functional scientific communication
Additional Technical Capabilities
3D printing and 3D CAD for experimental prototyping and custom hardware development