Cognitive load refers to the amount of effort required by an indi- vidual to process information. Dating back more than fifty years, the cognitive psychology community has conducted experiments showing that the cognitive load experienced by an individual can be measured using sub-millimeter fluctuations in their pupil size, assessed using medical grade infrared devices known as pupil- lometers, and more recently, infrared eye-trackers. However the cost and availability of these eye-trackers limits most pupil re- sponse measurement to laboratory settings. We argue that ubiqui- tously measuring pupillary response could transform the next generation of context aware computing applications—enabling computational devices to understand a user’s current ability to process information, especially for users with cognitive disabili- ties. To this end, we present PupilWare, a system that analyzes pupil size changes through commodity cameras like those in a laptop. We evaluate PupilWare’s ability to measure changes in pupil dilation using classic cognitive psychology experiments and validate its performance compared to infrared gaze trackers and medical grade pupillometers. We conclude that, in controlled conditions, PupilWare is as accurate as infrared eye-tracking for assessing task evoked cognitive load, though has problems with dark eyed individuals and eyelid occlusion.