The primary goal of the Real-Time Science Lab is to answer difficult scientific questions by modeling and manipulating human systems as they happen and at the speed at which they occur. Our approach uses modern computational and statistical tools (that is, data mining) to model dense longitudinal data from wearable physiological monitors, video processing tools, and ecological momentary assessment (called EMA).

This approach has wide applicability, but we focus on human systems in intricate situations like dyadic and multiperson interaction, and emotionally challenging cases like addiction recovery and psychopathology where emotion, context, and social factors are especially important.

We have several ongoing projects that focus on these themes, including the Wear-IT project for real time data collection and analysis and adaptive assessment and intervention delivery; the MID/DLE project for distributed privacy; and the Rapport project, which studies affect during interactions between individuals.