Prof. Dr. Xilei Dai | Engineering | Young Scientist Award
Professor | Chongqing University | China
Prof. Dr. Xilei Dai is a distinguished faculty member at the School of Architecture and Urban Planning, Chongqing University, with recognized expertise in the fields of smart building control, energy optimization, and sustainable building technologies. His academic profile is well established with 2,206 citations by 2,085 documents, 38 documents published, and an h-index of 17, demonstrating the strong impact and relevance of his research. He has influential publications in top-tier journals such as Applied Energy, Building Simulation, Building and Environment, and Energy and Buildings. One of his highly influential papers on green building has been widely acknowledged by peers, earning significant citations and recognition as an ESI highly cited work. His editorial contributions include serving as an associate editor for the Journal of Renewable and Sustainable Energy, further underlining his commitment to advancing knowledge in renewable energy and sustainability. Prof. Dr. Xilei Dai research focuses on building decarbonization strategies by integrating IoT-based technologies, artificial intelligence control systems, distributed energy resources, and battery storage, offering impactful solutions that reduce both energy consumption and carbon emissions. He has successfully led innovative projects such as the development of NetZero Building Energy Management Systems through AI-driven HVAC system control, reflecting his dedication to creating practical solutions with far-reaching implications for sustainable urban development. His research not only addresses pressing environmental challenges but also bridges the gap between optimization theory and real-world applications in energy system economics. With an expanding body of highly cited work, editorial leadership, and a strong focus on innovative building energy systems, Prof. Dr. Xilei Dai continues to contribute significantly to the global effort of achieving smart, efficient, and environmentally responsible building environments.
Featured Publications
Cao, X., Dai, X., & Liu, J. (2016). Building energy-consumption status worldwide and the state-of-the-art technologies for zero-energy buildings during the past decade. Energy and Buildings, 128, 198–213.
Dai, X., Liu, J., & Zhang, X. (2020). A review of studies applying machine learning models to predict occupancy and window-opening behaviours in smart buildings. Energy and Buildings, 223, 110159.
Liu, J., Dai, X., Li, X., Jia, S., Pei, J., Sun, Y., Lai, D., Shen, X., Sun, H., Yin, H., … (2018). Indoor air quality and occupants’ ventilation habits in China: Seasonal measurement and long-term monitoring. Building and Environment, 142, 119–129.
Dai, X., Huang, L., Qian, Y., Xia, S., Chong, W., Liu, J., Ieva, A. D., Hou, X., & Ou, C. (2020). Deep learning for automated cerebral aneurysm detection on computed tomography images. International Journal of Computer Assisted Radiology and Surgery, 15, 715–723.
Dai, X., Liu, J., Li, X., & Zhao, L. (2018). Long-term monitoring of indoor CO2 and PM2.5 in Chinese homes: Concentrations and their relationships with outdoor environments. Building and Environment, 144, 238–247.