We present a model for inferring where users look during interaction based on keypress data only. Given a key log, it outputs a scanpath that tells, moment-by-moment, how the user had moved eyes while entering those keys. The model can be used as a proxy for human data in cases where collecting real eye tracking data is expensive or impossible. Our technical insight is an inference architecture that considers the individual characteristics of the user, inferred as a low-dimensional parameter vector. We present a novel loss function for synchronizing inferred eye movements with the keypresses. Evaluations on touchscreen typing demonstrate accurate gaze inference.