Data Science in Large-scale Oral Health Study (Athens, GA)

This project addresses the critical public health challenge of Periodontal Disease (PD), particularly its intensification in patients with comorbidities like obesity and prediabetes. The intern will work to overcome significant statistical barriers—such as complex multi-dimensional data structures and high rates of missing data due to tooth loss—to conduct a comprehensive analysis of large-scale oral health databases. The primary goal is to develop novel, scalable Bayesian and machine learning methods that handle mixed-type longitudinal data to advance the understanding of how systemic inflammation influences oral health outcomes.

The intern’s efforts will focus on two key practical deliverables: the construction of a rigorously validated predictive modeling framework to forecast tooth loss and the development of an interactive, web-based prototype application. This application will allow clinicians and researchers to input patient-level covariates to obtain individualized risk predictions and visualize disease trajectories. By translating complex technical findings into actionable clinical tools, the project aims to bridge individual-level precision with population-based periodontal care across Georgia and the Southeast region.