Buildings are responsible for a significant portion of energy consumption in the US, accounting for more than 40% of US primary energy consumption. Heating, ventilation and air-conditioning (HVAC) accounts for nearly 50% of that use. Conditioning buildings is important since people spend 87% of their time in the place they live (residential) and the place they work (commercial). Despite this massive expense, many users are dissatisfied with the thermal conditions in buildings. Savings made in HVAC systems, therefore, have a major impact on energy consumption and cost, together with the reduction of greenhouse emissions for the nation. Equally critical is to provide thermal quality of service to their users, so people are comfortable in the place they reside and work.In this paper, we explore the tradeoff between commercial building HVAC energy consumption and the quality of thermal conditioning provided to users. We argue that optimal HVAC control cannot be achieved due to lack of critical information, namely where the users are inside the building, what do they want with respect to thermal comfort and how each zone responds to thermal changes. In this work, we present OFFICE, a model predictive control (MPC) framework for smart building HVAC control. The framework has several components that help to address the current HVAC control systems shortcomings, including (a) occupancy sensing in real-time, (b) occupancy prediction models based on historical occupancy data, (c) human-in-the-loop comfort feedback, (d) data-driven thermodynamic building models, and (e) weather forecasting data. All these components provide the necessary input to our model predictive control optimization framework that minimizes monetary costs in energy use while maintaining quality comfort bounds for the building’s users based on real-time user’s feedback. We developed a large system that involves all the above components, replacing the Building Management System control algorithms, taking over full control of the HVAC system. We tested OFFICE in a real LEED Gold certified university building with over 20 workers performing their daily tasks for 4 weeks, and we showed that we could obtain monetary costs savings of more than 10% while at the same time reducing the users’ dissatisfaction levels with thermal comfort from 25% to 0% dissatisfaction, significantly improving the quality of thermal service provided to the building’s users.