PENG ZHOU(周鵬)
Associate Professor (長聘副教授)
PhD, Construction Management, University of Illinois at Urbana-Champaign (UIUC)
Master, Construction Management, UIUC ? ?? ?
Contact
Central University of Finance and Economics
Shahe Higher Education Park, Beijing, China 102206
Office: Building 4, Room 336
Email: zhoupeng@cufe.edu.cn; pzhoucufe@163.com
Research interests
Low Carbon Emission and Energy Efficiency of Buildings, Big Data Analytics, Smart City, Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Natural Language Processing.
本課題組專注于城市更新與“碳達(dá)峰碳中和”雙碳背景下人工智能技術(shù)的建筑低碳與節(jié)能管理應(yīng)用研究。即在城市宏觀尺度下，應(yīng)用人工智能方法（如計(jì)算機(jī)視覺、深度學(xué)習(xí)、自然語言處理等算法），計(jì)算、模擬、預(yù)測城市建筑碳排放，實(shí)現(xiàn)未來城市規(guī)劃多目標(biāo)約束下（經(jīng)濟(jì)、法規(guī)、人口、城市功能等）的建筑形態(tài)特征低碳智能優(yōu)化。
歡迎對應(yīng)用機(jī)器學(xué)習(xí)、深度學(xué)習(xí)、計(jì)算機(jī)視覺、自然語言處理技術(shù)解決建筑低碳與節(jié)能管理領(lǐng)域問題感興趣的學(xué)生（不限專業(yè)，有計(jì)算機(jī)相關(guān)基礎(chǔ)優(yōu)先）報(bào)考加入我的研究課題組。
Appointments
Associate Professor, Department of Management Science and Engineering, Central University of Finance and Economics ?? ?
Teaching
Introduction to Building Information Modeling (undergraduate)
Automated Cost Estimation (undergraduate)
Engineering Risk Management (undergraduate)
Infrastructure Investment and Development (graduate)
Professional English (graduate)
Publications
Zhou P., Qi, Y.F., Yang, Q., and Chang, Y. (2025). “Neural topic modeling of machine learning applications in building: Key topics, algorithms, and evolution pattern.” Autom. Constr., 10.1016/j.autcon.2024.105890. (SCI, JCR Q1, 中科院一區(qū)Top)
Zhou P., Zhang, T., Zhao, L., Qi, Y., Chang, Y., and Bai, L. (2023). “Pre-clustering active learning method for automatic classification of building structures in urban areas.” Eng. Appl. Artif. Intell., 10.1016/j.engappai.2023.106382. (SCI, JCR Q1, 中科院一區(qū)Top)
Zhou, P., and El-Gohary, N. (2022). “Semantic information extraction of energy requirements from contract specifications: Dealing with complex extraction tasks.” J. Comput. Civ. Eng., 10.1061/(ASCE)CP.1943-5487.0001008. (SCI, JCR Q1, 中科院二區(qū))
Zhang, Q., Xue, C., Zhou, P., Wang, X., Zhang, J., and Su, X. (2022). “Named entity recognition for Chinese construction documents based on conditional random field.” Frontiers Eng. Manage. (FMS B, JCR Q1, 中科院二區(qū))
Zhou, P., and El-Gohary, N. (2021). “Semantic information alignment of BIMs to computer-interpretable regulations using ontologies and deep learning.” Adv. Eng. Inform., 10.1016/j.aei.2020.101239. (SCI, JCR Q1, 中科院一區(qū)Top)
Zhou, P., and Chang, Y. (2021). “Automated classification of building structures for urban built environment identification using machine learning.” J. Build. Eng., 10.1016/j.jobe.2021.103008, 04015057. (SCI, JCR Q1, 中科院二區(qū)Top)
Zhou, P., and El-Gohary, N. (2017). “Ontology-based automated information extraction from building energy conservation codes.” Autom. Constr., 10.1016/j.autcon.2016.09.004. (SCI, JCR Q1, 中科院一區(qū)Top)
Zhou, P., and El-Gohary, N. (2015). “Domain-specific hierarchical text classification for supporting automated environmental compliance checking.” J. Comput. Civ. Eng., 10.1061/(ASCE)CP.1943-5487.0000513, 04015057. (SCI, JCR Q1, 中科院二區(qū))
Zhou, P., and El-Gohary, N. (2015). “Ontology-based multi-label text classification for construction regulatory documents.” J. Comput. Civ. Eng., 10.1061/(ASCE)CP.1943-5487.0000530, 04015058. (SCI, JCR Q1, 中科院二區(qū))
Yu, J., Yang, F., Zhou, P., Li, Y., Huang, Z., and El-Gohary, N. (2021). “Curriculum system design for construction management major in finance and economics colleges facing the intelligent construction era.” International Conference on Construction and Real Estate Management 2021, ASCE, Reston, VA, 416-424. (EI)
Zhou, P., and El-Gohary, N. (2018). “Text and information analytics for fully automated energy code checking.” Proc. 2nd GeoMEast Int. Congress and Exhibition on Sustainable Civil Infrastructures, Springer International Publishing, Cham, Switzerland, 196-208. (EI)
Zhou, P., and El-Gohary, N. (2018). “Automated matching of design information in BIM to regulatory information in energy codes.” Proc. 2018 ASCE Construction Research Congress (CRC), ASCE, Reston, VA, 75-85. (EI)
Zhou, P., and El-Gohary, N. (2016). “Automated extraction of environmental requirements from contract specifications.” Proc. 16th Int. Conf. on Comput. in Civ. and Build. Eng. (ICCCBE2016), International Society for Computing in Civil and Building Engineering (ISCCBE), Osaka, Japan, 1669-1676. (EI)
Zhou, P., and El-Gohary, N. (2015). “Ontology-based information extraction from environmental regulations for supporting environmental compliance checking.” Proc. 2015 ASCE Int. Workshop Comput. Civ. Eng., ASCE, Reston, VA, 190-198. (EI)
Zhou, P., and El-Gohary, N. (2014). “Ontology-based multi-label text classification for enhanced information retrieval for supporting automated environmental compliance checking.” Proc. Comput. in Civ. and Build. Eng. (2014), ASCE, Reston, VA, 2238-2245. (EI)
Zhou, P., and El-Gohary, N. (2014). “Semantic-based text classification of environmental regulatory documents for supporting automated environmental compliance checking in construction.” Proc. 2014 ASCE Construction Research Congress (CRC), ASCE, Reston, VA, 897-906. (EI)
Research project
National Natural Science Foundation of China
Elite Scholars Support Program of Central University of Finance and Economics
Professional services
Reviewer：Journal of Computing in Civil Engineering, Journal of Environmental Management, Journal of Building Engineering, Building and Environment, Automation in Construction, International Journal of Construction Management, China Civil Engineering Journal
Committee：Data Sensing and Analysis (DSA) committee, Visualization, Information Modeling and Simulation (VIMS) committee, American Society of Civil Engineers (ASCE), TRB Information Systems in Construction Management Subcommittee. 中華建設(shè)管理研究會(CRIOCM)青年工作委員會委員. 中國城市經(jīng)濟(jì)學(xué)會基礎(chǔ)設(shè)施與運(yùn)維管理專業(yè)委員會委員.
Recruitment
Graduate students with major, talents or interest in application of machine learning, deep learning, computer vision, and natural language processing techniques to engineering management domain are welcome to join my research team.
