Mirosław Skibniewski

University of Maryland, College Park, United States
Professor
Department of Civil & Environmental Engineering

Scopus ID: 7004024216
Researcher ID: P-5310-2018
Google Scholar profile: link
ORCID ID: http://orcid.org/0000-0002-7102-753X

Selected Publications:

  1. Wu, X., Cao, Y., Liu, W., He, Y., Xu, G., Chen, Z.-S., Liu, Y., Skibniewski, M. J. (2023). BIM-driven building greenness evaluation system: An integrated perspective drawn from model data and collective experts’ judgments. Journal of Cleaner Production, 406, 136883. doi: https://doi.org/10.1016/j.jclepro.2023.136883

  2. Xiong, S.-H., Zhu, C.-Y., Chen, Z.-S., Deveci, M., Chiclana, F., Skibniewski, M. J. (2023). On extended power geometric operator for proportional hesitant fuzzy linguistic large-scale group decision-making. Information Sciences, 632, 637–663. doi: https://doi.org/10.1016/j.ins.2023.03.001

  3. Chen, H., Li, X., Feng, Z., Wang, L., Qin, Y., Skibniewski, M. J., Chen, Z.-S., Liu, Y. (2023). Shield attitude prediction based on Bayesian-LGBM machine learning. Information Sciences, 632, 105–129. doi: https://doi.org/10.1016/j.ins.2023.03.004

  4. Yuan, J., Zeng, A. Y., Skibniewski, M. J., Li, Q. (2009). Selection of performance objectives and key performance indicators in public–private partnership projects to achieve value for money. Construction Management and Economics, 27 (3), 253–270. doi: https://doi.org/10.1080/01446190902748705

  5. Zhang, L., Wu, X., Skibniewski, M. J., Zhong, J., Lu, Y. (2014). Bayesian-network-based safety risk analysis in construction projects. Reliability Engineering & System Safety, 131, 29–39. doi: https://doi.org/10.1016/j.ress.2014.06.006

  6. Nitithamyong, P., Skibniewski, M. J. (2004). Web-based construction project management systems: how to make them successful? Automation in Construction, 13 (4), 491–506. doi: https://doi.org/10.1016/j.autcon.2004.02.003

  7. Jang, W.-S., Healy, W. M., Skibniewski, M. J. (2008). Wireless sensor networks as part of a web-based building environmental monitoring system. Automation in Construction, 17 (6), 729–736. doi: https://doi.org/10.1016/j.autcon.2008.02.001