While people can typically make a rapid assessment of another person’s interruptibility, current systems generally have no way to consider whether an interruption is appropriate.  Current systems therefore tend to interrupt at inappropriate times or unduly demand attention. In this talk, James Fogarty, Carnegie Mellon University, presents his work examining the feasibility and robustness of sensor-based statistical models of human interruptibility. Fogarty has conducted a series of studies to explore the utility of a number of potential sensors, examine human ability to estimate interruptibility, deploy and evaluate actual sensors in office work environments, and develop models of task engagement based on low-level event streams. From the Series:CSE Colloquia - 2006