Ben Allen, Ph.D.

I study how social, behavioral, environmental, and biological contexts shape cardiometabolic health and everyday health behaviors. My research combines explainable, domain‑informed machine learning with methods from health psychology and public health to model obesity, diabetes, blood pressure, sleep, and physical activity across individuals, campuses, neighborhoods, and populations.
A central goal of this work is to make AI useful and trustworthy for health. I focus on identifying interpretable risk patterns, examining mechanisms such as health literacy and self‑efficacy, and evaluating whether personalized recommendations are plausible, robust, and actionable. Ultimately, my research aims to translate complex health data into insights that can guide prevention and intervention where people live, learn, and receive care.