Kym McCormick

With a foundational background in behavior modeling and eyewitness identification, my research bridges psychological modeling techniques and public health. Initially trained in developing mathematical models for eyewitness identification decisions, I transitioned to oral health research to address pressing gaps in understanding and diagnosing periodontitis. My work focuses on applying advanced modeling techniques to track disease progression at a granular, tooth-specific level. By leveraging predictive machine learning and spatial network models, I aim to improve the precision of periodontitis diagnostics and risk prediction, moving toward a more individualized approach to oral health.

My experience in behavior modeling informs my approach to understanding complex disease patterns, particularly where patient behavior, health outcomes, and environmental factors intersect. This interdisciplinary perspective supports my goal of refining diagnostic tools within oral health and developing more representative population health models. My research aligns with my commitment to applying robust, data-driven methods to solve real-world health issues and improve outcomes across patient demographics.