Byunggul “BG” Lim, Ph.D., is a Postdoctoral Research Associate at the Texas A&M AgriLife Institute for Advancing Health through Agriculture, IHA. His research focuses on leveraging mobile health, mHealth, technologies and machine learning to promote physical activity and improve cardiometabolic health.
Lim received his doctoral training in exercise physiology, where he conducted digital exercises intervention research among breast cancer survivors using motion recognition–based exercise programs – e.g., Kinect-enabled systems. He subsequently applied machine learning approaches to these data to model behavioral and physiological responses, which laid the foundation for his current research integrating digital health data and computational methods.
His current work integrates data from wearable sensors, continuous glucose monitoring and ecological momentary assessment to model dynamic behavioral and physiological processes in daily life. He develops machine learning models to predict glucose excursions and identify moments of vulnerability or opportunity for behavioral change, such as physical activity lapses and suboptimal dietary behaviors. Building on these predictive models, he designs and tests behavioral interventions, including Just-In-Time Adaptive Interventions, that deliver personalized, context-aware support to reduce sedentary behavior and optimize physical activity in real time.
Lim’s long-term goal is to advance precision behavioral interventions by integrating digital health data streams with computational modeling to enable scalable, real-time strategies for improving cardiometabolic outcomes.