研究方向为建成环境与能源技术、人工智能、控制工程的多学科交叉领域。部分代表性论文如下： Fang, J., Yan, C., Lu, W., Shi, J., Xu, L., Hu, K., ... & Zhuang, C.* (2025). Embedding physical neurons in physics-informed neural networks (EP-PINNs) for enhancing chiller performance prediction. Building Simulation, 1-25. https://link.springer.com/10.1007/s12273-025-1293-z Zhuang C., Choudhary R., Mavrogianni A. (2023). Uncertainty-based optimal energy retrofit methodology for building heat electrification with enhanced energy flexibility and climate adaptability. Applied Energy, 341: 121111. https://doi.org/10.1016/j.apenergy.2023.121111. Zhuang C., Choudhary R., Mavrogianni A. (2022). Probabilistic occupancy forecasting for risk-aware optimal ventilation through autoencoder Bayesian deep neural networks. Building and Environment, 219: 109207.https://doi.org/10.1016/j.buildenv.2022.109207. Zhuang C., Shan K, Wang S. (2021). Coordinated demand-controlled ventilation strategy for energy-efficient operation in multi-zone cleanroom air-conditioning systems. Building and Environment, 191: 107588.https://doi.org/10.1016/j.buildenv.2021.107588. Zhuang C., Gao Y, Zhao Y., Levinson R., Heiselberg P., Wang Z., Guo R. (2021). Potential benefits and optimization of cool-coated office buildings: A case study in Chongqing, China. Energy, 226: 120373. https://doi.org/10.1016/j.energy.2021.120373. Zhuang C., Wang S. and Shan K. (2020). A risk-based robust optimal chiller sequencing control strategy for energy-efficient operation considering measurement uncertainties. Applied Energy, 280: 115983.https://doi.org/10.1016/j.apenergy.2020.115983. Zhuang C., and Wang S. (2020). An adaptive full-range decoupled ventilation strategy for buildings and spaces requiring strict humidity control and its applications in different climatic conditions. Sustainable Cities and Society, 52: 101838. https://doi.org/10.1016/j.scs.2019.101838. Zhuang C. and Wang S. (2020). Uncertainty-based robust optimal design of cleanroom air-conditioning systems considering life-cycle performance. Indoor and Built Environment, 29 (9): 1214-1226.https://doi.org/10.1177/1420326X19899442. Zhuang C. and Wang S. (2020). Risk-based online robust optimal control of air-conditioning systems for buildings requiring strict humidity control considering measurement uncertainties. Applied Energy, 261: 114451.https://doi.org/10.1016/j.apenergy.2019.114451. Zhuang C., Wang S., Shan K. (2019). Probabilistic optimal design of cleanroom air-conditioning systems facilitating optimal ventilation control under uncertainties. Applied Energy, 253: 113576. https://doi.org/10.1016/j.apenergy.2019.113576. Zhuang C., Wang S., Shan K. (2019). Adaptive full-range decoupled ventilation strategy and air-conditioning systems for cleanrooms and buildings requiring strict humidity control and their performance evaluation. Energy, 168:883-896.https://doi.org/10.1016/j.energy.2018.11.147. Shi D., Gao Y., Zeng P., Li B., Shen P., Zhuang C.* (2022). Climate adaptive optimization of green roofs and natural night ventilation for lifespan energy performance improvement in office buildings. Building and Environment, 223:109505. https://doi.org/10.1016/j.buildenv.2022.109505. Guo R., Gao Y., Zhuang C.*, Heiselberg P., Levinson R., Zhao X., Shi D. (2020). Optimization of cool roof and night ventilation in office buildings: A case study in Xiamen, China. Renewable Energy, 147: 2279-2294. https://doi.org/10.1016/j.renene.2019.10.032. | 
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