| Individual difference in thermal comfort: A literature review Z Wang, R de Dear, M Luo, B Lin, Y He, A Ghahramani, Y Zhu Building and Environment 138, 181-193, 2018 | 555 | 2018 |
| Reinforcement learning for building controls: The opportunities and challenges Z Wang, T Hong Applied Energy 269, 115036, 2020 | 382 | 2020 |
| Building thermal load prediction through shallow machine learning and deep learning Z Wang, T Hong, MA Piette Applied Energy 263, 114683, 2020 | 314 | 2020 |
| A review of operating performance in green buildings: Energy use, indoor environmental quality and occupant satisfaction Y Geng, W Ji, Z Wang, B Lin, Y Zhu Energy and Buildings 183, 500-514, 2019 | 303 | 2019 |
| State-of-the-art on research and applications of machine learning in the building life cycle T Hong, Z Wang, X Luo, W Zhang Energy and Buildings 212, 109831, 2020 | 259 | 2020 |
| Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications H Li, Z Wang, T Hong, MA Piette Advances in Applied Energy 3, 100054, 2021 | 227 | 2021 |
| Human metabolic rate and thermal comfort in buildings: The problem and challenge M Luo, Z Wang, K Ke, B Cao, Y Zhai, X Zhou Building and Environment 131, 44-52, 2018 | 193 | 2018 |
| Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives G Pinto, Z Wang, A Roy, T Hong, A Capozzoli Advances in Applied Energy 5, 100084, 2022 | 164 | 2022 |
| Evaluation and comparison of thermal comfort of convective and radiant heating terminals in office buildings B Lin, Z Wang, H Sun, Y Zhu, Q Ouyang Building and Environment 106, 91-102, 2016 | 161 | 2016 |
| Thermal comfort evaluated for combinations of energy-efficient personal heating and cooling devices M Luo, E Arens, H Zhang, A Ghahramani, Z Wang Building and Environment 143, 206-216, 2018 | 138 | 2018 |
| High-density thermal sensitivity maps of the human body M Luo, Z Wang, H Zhang, E Arens, D Filingeri, L Jin, A Ghahramani, ... Building and environment 167, 106435, 2020 | 119 | 2020 |
| Indoor climate experience, migration, and thermal comfort expectation in buildings M Luo, Z Wang, G Brager, B Cao, Y Zhu Building and Environment 141, 262-272, 2018 | 115 | 2018 |
| Investigation of winter indoor thermal environment and heating demand of urban residential buildings in China's hot summer–Cold winter climate region B Lin, Z Wang, Y Liu, Y Zhu, Q Ouyang Building and Environment 101, 9-18, 2016 | 109 | 2016 |
| Residential heating energy consumption modeling through a bottom-up approach for China's Hot Summer–Cold Winter climatic region Z Wang, Z Zhao, B Lin, Y Zhu, Q Ouyang Energy and Buildings 109, 65-74, 2015 | 100 | 2015 |
| Data fusion in predicting internal heat gains for office buildings through a deep learning approach Z Wang, T Hong, MA Piette Applied Energy 240, 386-398, 2019 | 98 | 2019 |
| Measured energy use and indoor environment quality in green office buildings in China B Lin, Y Liu, Z Wang, Z Pei, M Davies Energy and Buildings 129, 9-18, 2016 | 91 | 2016 |
| Generating realistic building electrical load profiles through the Generative Adversarial Network (GAN) Z Wang, T Hong Energy and Buildings 224, 110299, 2020 | 88 | 2020 |
| Revisiting individual and group differences in thermal comfort based on ASHRAE database Z Wang, H Zhang, Y He, M Luo, Z Li, T Hong, B Lin Energy and Buildings 219, 110017, 2020 | 88 | 2020 |
| Dimension analysis of subjective thermal comfort metrics based on ASHRAE Global Thermal Comfort Database using machine learning Z Wang, J Wang, Y He, Y Liu, B Lin, T Hong Journal of Building Engineering 29, 101120, 2020 | 87 | 2020 |
| The uncertainty of subjective thermal comfort measurement J Wang, Z Wang, R de Dear, M Luo, A Ghahramani, B Lin Energy and Buildings 181, 38-49, 2018 | 87 | 2018 |
