Work
Statistical models, interactive tools, and data pipelines at the intersection of neurological research and infectious disease.
An interactive Shiny dashboard comparing resting-state EEG biomarkers between Mild Cognitive Impairment (MCI) and Alzheimer’s Disease patients. Built using R Shiny and flexdashboard with data from the Goizueta Brain Health Institute at Emory University.
A Bayesian hierarchical model in Stan to characterize viral shedding dynamics by integrating heterogeneous lab measurements, including viral load and Ct values. Accounts for censoring and estimates a shared latent viral trajectory.
Literature review to identify individual-level longitudinal viral shedding datasets. Manual extraction combined with an LLM-powered pipeline to parse data into standardized YAML files, building a benchmark dataset for AI training and validation.