Carnegie Mellon University

Pingbo Tang

Pingbo Tang (E 2009)

Associate Professor, Civil and Environmental Engineering

Address
5000 Forbes Avenue
Pittsburgh, PA 15213

Bio

Pingbo Tang, Ph.D., is an associate professor in the Department of Civil and Environmental Engineering. He founded and is directing Spatiotemporal Workflows and Resilient Management Laboratory (SWARM Lab). He obtained his Bachelor Degree of Civil Engineering in 2002, and his Master Degree of Bridge Engineering in 2005, both from Tongji University, Shanghai, China. He obtained is PhD from the group of Advanced Infrastructure Systems (AIS) at Carnegie Mellon University in 2009.

Tang’s research explores the remote sensing, human systems engineering, data analytics, and information modeling technology to support spatiotemporal analyses needed for predictive management of constructed facilities, workspaces and civil infrastructure systems. His on-going studies have been examining sensing and modeling methods for comprehending the Human-Cyber-Physical-Systems (H-CPS) in accelerated construction and infrastructure operations (e.g., airport operations, nuclear plant outage control). He has published more than 100 peer-reviewed articles in these areas. The National Science Foundation (NSF), Department of Energy (DOE), The National Aeronautics and Space Administration (NASA), Salt River Project (SRP), and Phoenix Government have funded his research efforts.

Tang holds memberships or leadership positions of the American Society of Civil Engineers (ASCE, the Chair of the ASCE Data Sensing and Analysis committee), TRB (Committee on Bridge Management, AHD35), IABSE, ASPRS, and ASTM International (Committee E57: 3D imaging systems). He is on the editorial board of ASCE Journal of Computing in Civil Engineering, as well as a reviewer of multiple top journals and conferences related to Computing in Civil Engineering. He won best paper awards on top conferences (the 2019 ASCE International Conference on Computing in Civil Engineering, the ASCE 2017 International Workshop on Computing in Civil Engineering, the ASCE 2009 Construction Research Congress), the best poster award of Construction Industry Institute's 2011 Annual Conference, the 2013 Recent Alumnus Achievement Award of the Civil and Environmental Engineering Department at Carnegie Mellon University. Tang won the National Science Foundation CAREER Award in 2015.

Education

PhD 2009 – Carnegie Mellon University
MS 2005 – Tongji University, China
BS 2002 – Tongji University, China

Research

Research Group: AIS

  • Computer vision, pattern recognition, and data science for civil infrastructure systems
  • Human technology and human systems engineering in civil engineering
  • Automation and robotics in construction and civil infrastructure operations

Publications

  • Liao, P.*, Wan, Y., Tang, P., Wu, C., Hu, Y., and Zhang, S. (2019). “Applying crowdsourcing techniques in urban planning: A bibliometric analysis of research and practice prospects.” Cities.
  • Kalasapudi, V. S., Tang, P.*, Xiong, W., and Shi, Y. (2018). “A multi-level 3D data registration approach for supporting reliable spatial change classification of single-pier bridges.” Advanced Engineering Informatics, Elsevier, 38, 187–202, DOI: 10.1016/j.aei.2018.06.010
  • Zhang, C., Tang, P.*, Cooke, N., Buchanan, V., Yilmaz, A., Germain, S.S., Boring, R.L., Akca-Hobbins, S., Gupta, A. (2017) “Human-Centered Automation for Resilient Nuclear Power Plant Outage Control.” Elsevier Journal of Automation in Construction, DOI: 10.1016/j.autcon.2017.05.001.
  • Kalasapudi, V. S., Tang, P.*, and Turkan, Y. (2017) “Computationally efficient change analysis of piece-wise cylindrical building elements for proactive project control." Elsevier Journal of Automation in Construction, DOI:10.1016/j.autcon.2017.04.001.
  • Zhang, C., Kalasapudi, V. S., and Tang, P.* (2016) “Rapid Data-Quality-Oriented 3D Imaging Planning for Dynamic Construction Environments.” Elsevier Journal of Advanced Engineering Informatics, Volume 30, Issue 2, April 2016, Pages 218–232, DOI:10.1016/j.aei.2016.03.004.