Residential building energy usage can be considered as being derived from the activity patterns of individuals inside the home. As such an activity-based energy demand model that can create in-home energy usage profiles from household activity patterns is the key to a better building energy demand analysis. In order to find the relation between building energy usage and activity profiles, energy usage data with an overlapping activity diary survey is needed. However, there is no detailed data containing information on both household activity schedules and energy usage. Therefore, utilizing a Bayesian approach, we explore the possibility of reverse engineering to get the household activity patterns from energy usage profiles. The findings can be further used for linking the domestic energy demand to the activity schedules of the occupants.