Recent advances in the areas of multimodal machine learning and artificial intelligence (AI)
have led to the development of challenging tasks at the intersection of Computer Vision …

This paper seeks to address ten questions that explore the burgeoning field of Human-
Building Interaction (HBI), an interdisciplinary field that represents the next frontier in …

While reinforcement learning (RL) is gaining popularity in energy systems control, its real-
world applications are limited due to the fact that the actions from learned policies may not …

Training and validating algorithms in a simulation testbed can accelerate research and
applications of optimal control of residential loads to improve energy flexibility and grid …

To integrate high amounts of renewable energy resources, electrical power grids must be
able to cope with high amplitude, fast timescale variations in power generation. Frequency …

Abstract Model Predictive Control (MPC) is extensively utilized for demand response (DR) in
commercial buildings. When deploying MPC in real buildings, the model uncertainty is …

Modern power systems require flexible demand-side resources to maintain the balance
between electricity supply and demand. Building thermostatically controlled loads (TCLs) …

The cooling systems contribute to 40% of overall building energy consumption. Each
building has different cooling requirements based on its usage. There are two types of …

The feasibility of collecting a large amount of expert demonstrations has inspired growing
research interests in learning-to-drive settings, where models learn by imitating the driving …

Residential buildings consume 4.4 quads of electricity annually, approximately 37% of the
total electricity consumption in the United States. This represents a vast resource that can be …