Circadian rhythms are endogenous oscillations of approximately 24 hours, which are largely entrained by the light/dark cycle. Understanding the rhythmic processes that determine circadian phase has many practical applications (related to jet lag, shift work, chronotherapy, and overall rest/alertness, for example). In this talk, we will detail the primary light-based ODE models that have been used to predict circadian phase in humans. We present some of our work in adapting these models to differing datasets and populations, including shift workers and cancer patients. Finally, we discuss alternate techniques to extract parameters of circadian rhythm from physiological data collected via wearable devices. Speaker(s): Caleb Meyer (University of Michigan)