Professor in the Department of Civil and Environmental Engineering
structural health monitoring; cyber-physical system architectures; infrastructure resilience; multifunctional nanocomposites; non-destructive evaluation; community engagement; academic leadership
Appointments and Affiliations
- Professor in the Department of Civil and Environmental Engineering
- Vinik Dean of Engineering
- Professor in the Department of Electrical & Computer Engineering
- Email Address: email@example.com
- B.S. The Cooper Union, 1997
- M.S.C.E. Stanford University, 1998
- Ph.D. Stanford University, 2002
- M.S.E.E. Stanford University, 2003
Research InterestsProf. 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.
- EGR 393: Research Projects in Engineering
In the News
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- Draughon, G., J. Lynch, and L. Salvino. “Integrated Vision-Body Sensing System for Tracking People in Intelligent Environments,” 253 LNCE:885–93, 2023. https://doi.org/10.1007/978-3-031-07254-3_89.
- Flanigan, K. A., and J. P. Lynch. “Optimal Event-Based Policy for Remote Parameter Estimation in Wireless Sensing Architectures Under Resource Constraints.” Ieee Transactions on Wireless Communications 21, no. 7 (July 1, 2022): 5293–5304. https://doi.org/10.1109/TWC.2021.3139289.
- Zhou, H., J. Lynch, and D. Zekkos. “Autonomous wireless sensor deployment with unmanned aerial vehicles for structural health monitoring applications.” Structural Control and Health Monitoring 29, no. 6 (June 1, 2022). https://doi.org/10.1002/stc.2942.
- Flanigan, K. A., M. Aguero, R. Nasimi, F. Moreu, J. P. Lynch, and M. Ettouney. “OBJECTIVE RESILIENCE MONITORING FOR RAILROAD SYSTEMS.” In Objective Resilience: Technology, 75–120, 2022. https://doi.org/10.1061/9780784415900.ch4.
- Flanigan, K. A., J. P. Lynch, and M. Ettouney. “Quantitatively linking long-term monitoring data to condition ratings through a reliability-based framework.” Structural Health Monitoring 20, no. 5 (September 1, 2021): 2376–95. https://doi.org/10.1177/1475921720949965.