Carnegie Mellon University

Katherine Flanigan

Katherine A. Flanigan

Assistant Professor, Civil and Environmental Engineering

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  • Porter Hall 123A
5000 Forbes Avenue
Pittsburgh, PA 15213


Katherine Flanigan is an Assistant Professor in the Department of Civil and Environmental Engineering at Carnegie Mellon University (CMU). Flanigan also holds a courtesy appointment in the Department of Electrical and Computer Engineering at CMU. She received her PhD in Civil Engineering from the University of Michigan in 2020. At the University of Michigan, Flanigan was an NSF Graduate Research Fellow, recipient of the College of Engineering Richard and Eleanor Towner Prize for Outstanding PhD Research, and received Master’s degrees in Civil Engineering in 2016 as well as Electrical and Computer Engineering in 2018. Flanigan received her Bachelor’s degree in Civil and Environmental Engineering from Princeton University in 2014.

Flanigan’s research draws upon tools and technologies from across disciplines (such as civil engineering, electrical engineering, and computer science) to transform traditional civil infrastructure and urban systems into “intelligent” and adaptable cyber-physical systems (CPS). She focuses on integrating sensing, computing, and actuation technologies to improve the performance, resilience, accessibility, and sustainability of infrastructure and urban systems. This includes, for example, developing novel wireless sensing technologies for smart city sensor networks, using CPS and modeling to track the health and resilience of critical infrastructure (at both single-asset and system levels), and leveraging cloud-based data management and analytics to control natural and physical urban systems.

Flanigan’s work also extends CPS to cyber-physical-social systems (CPSS) by explicitly integrating human interaction, including responses to physical and cyber CPS elements. CPSS accounts for the interdependencies between physical and social systems (human-infrastructure interactions), which are becoming increasingly evident due to technological advancements that have introduced new components of social interaction when services are embedded within infrastructure systems. Her research aims to overcome both technical and social challenges to developing CPSS. This includes projects focused on integrating human-centric data and human-in-the-loop control solutions as well as understanding the role that CPS elements can play in promoting equity by deeply rooting policy-making and governance within community-driven data collection.


Ph.D. - Civil Engineering Intelligent Systems, University of Michigan, 2020
M.S.E. - Electrical and Computer Engineering, University of Michigan, 2018
M.S.E. - Civil Engineering, University of Michigan, 2016
B.S.E. - Civil and Environmental Engineering, Princeton University, 2014


Research Group: IESS, SETS, CREST

Select Publications

Flanigan, K.A., and Lynch, J.P. Optimal event-based policy for remote parameter estimation in wireless sensing architectures under resource constraints. IEEE Transactions on Wireless Communications, 2022, doi: 10.1109/TWC.2021.3139289.

Flanigan, K.A., Handley, J., Lynch, J.P., et al. Open urban sensing architecture for community-governed smart and connected communities. Submitted to Sustainable Cities and Society.

Flanigan, K.A., Lynch, J.P., and Ettouney, M. Quantitatively linking long-term monitoring data to condition ratings through a reliability-based framework. Journal of Structural Health Monitoring, 2020, doi: 10.1177/1475921720949965.

Flanigan, K.A., Lynch, J.P., and Ettouney, M. Probabilistic fatigue assessment of monitored railroad bridge components using long-term response data in a reliability framework. Journal of Structural Health Monitoring, 2020, doi: 10.1177/1475921720915712.

Flanigan, K.A., Aguero, M., Nasimi R., et al. Objective resilience monitoring for railroad systems. In: Mohammed Ettouney (ed) ASCE Objective Resilience Manual of Practice, ASCE Press, 2020.


Flanigan K.A., and Lynch J.P. Urbano wireless sensing architecture for smart city sensor networks. Invention Disclosure #7741, 2017.


  • 12-200 CEE Challenges
  • 12-774 Foundations of Intelligent Infrastructure Systems