Taming the Flood
24 January 2025
Williams Family Associate Professor Iris Tien is helping coastal communities improve their resilience with the right flood-control infrastructure in the right places.
Williams Family Associate Professor
Biography
Dr. Iris Tien is Williams Family Associate Professor in the School of Civil and Environmental Engineering at the Georgia Institute of Technology. She joined the faculty in 2014 after receiving her Ph.D. in Civil Systems Engineering from the University of California, Berkeley. Dr. Tien’s research interests are in probabilistic methods for modeling and reliability assessment of civil infrastructure systems. Her research leverages her unique interdisciplinary expertise encompassing traditional topics of civil engineering, sensing and data analytics, stochastic processes, probabilistic risk assessment, and decision making under uncertainty. Dr. Tien’s research has been funded by the National Science Foundation, Department of Homeland Security, U.S. Department of Transportation, and National Institute of Standards and Technology. Her work on interdependent infrastructure systems modeling and analysis has twice won 1st Place Paper Awards in resilient critical infrastructure.
Dr. Tien was selected by the National Academy of Engineering to organize the session on Resilient and Reliable Infrastructure at the U.S. Frontiers of Engineering Symposium; and speak on Community Resilience at the National Academies Frontiers of Science, Engineering, and Medicine Symposium. Dr. Tien was awarded the prestigious Early Achievement Research Prize by the International Association for Structural Safety and Reliability (IASSAR), and her published work has been recognized as Editor’s Choice Selection Papers in multiple journals, including the ASCE Journal of Infrastructure Systems, ASCE Journal of Water Resources Planning and Management, and the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems.
Research
Dr. Tien’s research interests include: probabilistic methods for modeling and reliability assessment of civil infrastructure systems; complex systems risk analysis; structural and infrastructure health monitoring; sensing and data analytics, signal processing, and machine learning; stochastic processes; and decision making under uncertainty; with applications for smart cities, interdependent systems, and resilient communities.
Education
Ph.D. in Civil Engineering Systems University of California, Berkeley 2014
M.S. in Civil and Environmental Engineering University of California, Berkeley 2010
B.S. in Civil Engineering University of California, Berkeley 2008
Teaching
Dr. Tien’s teaching interests include: risk assessment, data analytics, structural reliability, and construction and infrastructure system engineering processes. She has created new courses in Engineering Risk Analysis and Data Analytics for CEE Systems, and has implemented numerous innovative course pedagogies and delivery methods into her courses.
Distinctions & Awards
- 2024 Editor’s Choice Selection Paper, ASCE Journal of Water Resources Planning and Management
- 2023 Cybersecurity Fellow, College of Engineering, Georgia Institute of Technology
- 2023 Institute Research Award for Outstanding Achievement in Advancing Diversity, Equity, and Inclusion in Research
- 2022 IASSAR Early Achievement Research Prize, International Association for Structural Safety and Reliability (IASSAR)
- 2022 Editor’s Choice Selection Paper, ASCE Journal of Infrastructure Systems
- 2019 Editor’s Choice Selection Paper, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems
- 2018 1st Place Paper Award, Critical Infrastructure, Resilience Week
- 2017 Smart Cities Fellow, Serve-Learn-Sustain, Georgia Institute of Technology
- 2017 1st Place Paper Award, Resilient Critical Infrastructure, Resilience Week
- 2016 Paul A. Duke GIFT Action Plan Achievement Mentor Award, Center for Education Integrating Science, Mathematics and Computing (CEISMC), Georgia Institute of Technology
Publications
- *Vargas, P., and Tien, I., “Anticipatory Risk Assessment and Mitigation for Water Distribution Infrastructure in Coastal Communities Subject to Sea Level Rise,” ASCE Journal of Infrastructure Systems, 2026
- Swinea, J., Tien, I., Stynoski, P., and Stewart, L., “Reliability-Based Evaluation of Cross-Laminated Timber (CLT) Ballistic Resistance for Performance Prediction and Design,” International Journal of Impact Engineering, Vol. 211, 2026
- *Herndon, H., and Tien, I., “Corrosion Assessment Using Computer Vision, Machine Learning, and Deep Learning on Imagery Data: Evaluation and Use for Bridge Inspections,” ASCE Journal of Bridge Engineering, Vol. 30, No. 12, pp 1-24, 2025
- *Herndon, H., and Tien, I., “Creating a First-Pass Algorithm for Corrosion Assessment in Bridge Inspections Using Machine Learning and UAV-Collected Imagery Data,” Structure and Infrastructure Engineering, pp. 1-15, 2025
- Smyl, D., Zhuang, B., Rigby, S., Bruun, E., Jones, B., Kastner, P., Tien, I., and Gallet A., “OpenPyStruct: Open-Source Toolkit for Machine Learning-Driven Structural Optimization,” Engineering Structures, Vol. 343, Part A, pp. 1-17, 2025
- Hyde, A., Alemdar, M., O’Connell, K., Omunga, P., *Reckner, M., Loukissas, Y., Tien, I., Yousufi, M., Botchwey, N., Chatman, O., Clayton, K., McClain, M., Shabazz, M., and Branch, B., “Promoting Youth Advocacy for Resilience to Disasters: A Pilot Study,” Gender and Development, Vol. 32, No. 3, pp. 749-772, 2024
- *Lozano, J., Tien, I., Nichols, E., and Frost, J., “Impact of Ground Motion Uncertainty Evolution from Post-Earthquake Data on Building Damage Assessment,” Earthquake Spectra, Vol. 40, No. 4, p. 2430-2455, 2024
- *Reckner, M., Tien, I., Smith, S., Omunga, P., Alemdar, M., and Hyde, A., “The Impact of Youth Education on Green Stormwater Infrastructure Recommendations to Increase Equity and Resilience in Marginalized Flood-Prone Communities,” ASCE Journal of Water Resources Planning and Management, Vol. 150, No. 9, 2024
- Xu, L., Taylor, J., and Tien, I., “Micromobility vs. Driving: How Air Quality Alerts Impact Transportation Choices,” ASCE Journal of Management in Engineering, Vol. 41, No. 1, 2024
- Salley, C., Mohammadi, N., Xie, J., Tien, I., and Taylor, J., “Assessing Community Needs in Disasters: Transfer Learning for Fusing Limited Georeferenced Data from Crowdsourced Applications on the Community Level,” ASCE Journal of Management in Engineering, Vol. 40, No. 6, pp. 1-16, 2024
- *Lozano, J., Nichols, E., Frost, J., and Tien, I., “Spatial and Temporal Evolution of Post-Disaster Data for Damage Assessment of Civil Infrastructure Systems,” Geomatics, Natural Hazards and Risk, Vol. 14, No. 1, 2023
- Al-Hasani, L., Perez, G., *Herndon, H., Park, J., Poole, J., Tien, I., Washburn, N., Cho, Y., Gentry, T., and Kurtis, K., “Prediction of Heat of Hydration of Cementitious Systems Using Gaussian Process Regression Enables Mass Concrete Thermal Modeling, Materials and Structures, Vol. 56, No. 45, pp. 1-19, 2023
- *Reckner, M., and Tien, I., “Community-Scale Spatial Mapping to Prioritize Green and Grey Infrastructure Locations to Increase Flood Resilience,” Sustainable and Resilient Infrastructure, Vol. 8, No. S1, pp. 289-310, 2023
- Tien, I., *Lozano, J., and *Chavan, A., “Locating Real-Time Water Level Sensors in Coastal Communities to Assess Flood Risk by Optimizing Across Multiple Objectives,” Nature Communications Earth and Environment, Vol. 4, No. 96, pp. 1-12, 2023
- *Vargas, P., and Tien, I., “Impacts of 5G on Cyber-Physical Risks for Interdependent Connected Smart Critical Infrastructure Systems,” International Journal of Critical Infrastructure Protection, Vol. 42, 2023
- *Lozano, J., and Tien, I., “Data Collection Tools for Post-Disaster Damage Assessment of Building and Lifeline Infrastructure Systems,” International Journal of Disaster Risk Reduction, Vol. 94, 2023
In the News
New Fellowships Support High-Impact Cybersecurity Research
10 May 2023
Williams Family Associate Professor Iris Tien is one of five faculty members selected to become Cybersecurity Fellows to help grow the College of Engineering’s work in high-impact cyber-physical systems security.
Tool Helps Coastal Areas Find Ideal Spots for Water Level Sensors
13 April 2023
A tool developed by Georgia Tech researchers can help pinpoint the ideal locations for water level sensors to maximize the real-time data available to emergency managers to help anticipate flood risks and respond in emergencies.