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Jerome Peter Lynch


Vinik Dean of Engineering

structural health monitoring; cyber-physical system architectures; infrastructure resilience; multifunctional nanocomposites; non-destructive evaluation; community engagement; academic leadership

Appointments and Affiliations

  • Fitzpatrick Family University Distinguished Professor of Engineering
  • Professor in the Department of Civil and Environmental Engineering
  • Vinik Dean of Engineering
  • Professor in the Department of Electrical & Computer Engineering

Contact Information

  • Email Address:


  • M.S.E.E. Stanford University, 2003
  • Ph.D. Stanford University, 2002
  • M.S.C.E. Stanford University, 1998
  • B.S. The Cooper Union, 1997

Research Interests

Prof. Lynch's research interests are in advancing cyber-physical system architectures that combine sensing, computing, and control to create intelligent civil infrastructure systems.  He is best known for his research portfolio in structural health monitoring (SHM) that allow the performance and health of civil infrastructure systems to be assessed based on monitoring data to improve system safety and resilience.

Courses Taught

  • EGR 393: Research Projects in Engineering

In the News

Representative Publications

  • Draughon, G; Lynch, J; Salvino, L, Integrated Vision-Body Sensing System for Tracking People in Intelligent Environments, vol 253 LNCE (2023), pp. 885-893 [10.1007/978-3-031-07254-3_89] [abs].
  • Flanigan, KA; Lynch, JP, Optimal Event-Based Policy for Remote Parameter Estimation in Wireless Sensing Architectures Under Resource Constraints, Ieee Transactions on Wireless Communications, vol 21 no. 7 (2022), pp. 5293-5304 [10.1109/TWC.2021.3139289] [abs].
  • Zhou, H; Lynch, J; Zekkos, D, Autonomous wireless sensor deployment with unmanned aerial vehicles for structural health monitoring applications, Structural Control and Health Monitoring, vol 29 no. 6 (2022) [10.1002/stc.2942] [abs].
  • Flanigan, KA; Aguero, M; Nasimi, R; Moreu, F; Lynch, JP; Ettouney, M, OBJECTIVE RESILIENCE MONITORING FOR RAILROAD SYSTEMS (2022), pp. 75-120 [10.1061/9780784415900.ch4] [abs].
  • Flanigan, KA; Lynch, JP; Ettouney, M, Quantitatively linking long-term monitoring data to condition ratings through a reliability-based framework, Structural Health Monitoring: an International Journal, vol 20 no. 5 (2021), pp. 2376-2395 [10.1177/1475921720949965] [abs].