Adrian Chong
Papers
1
Total Citations
6
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1
About
Adrian Chong is a leading researcher in the field of building performance simulation and indoor environmental quality (IEQ), with a particular focus on integrating data-driven modeling with physical building systems. His work bridges the gap between high-fidelity simulation and real-world sensing, advancing how we understand and optimize the spaces where people live and work. Chong is best known for pioneering the use of Gaussian Process Regression for spatiotemporal modeling of thermal comfort and air quality, as demonstrated in his highly cited 2025 paper, which has already garnered 6 citations. This work introduces mobile sensing as a practical tool for capturing dynamic IEQ conditions, moving beyond static sensor networks. His broader contributions include developing methods for calibrating building energy models and quantifying uncertainty in simulation outputs, directly impacting how engineers design more efficient and comfortable buildings. Through his research, Chong has become a key voice in the push toward smarter, more responsive built environments, making his work essential reading for students and researchers in building science, data analytics, and sustainable design.
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Top Papers
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