CSIS Seminar

Toward Resilience of Civil Infrastructures: Machine Learning-based Probabilistic Assessment

Abstract

Civil infrastructures serve as the critical lifeline to connect communities with essential services for public health, economic productivity, and the operation of daily life. Disruption of critical infrastructure can cause devastating social and economic consequences, particularly in a catastrophic event such as an earthquake. With the increasing demand for improved infrastructure services in modern societies, establishing resilient infrastructure is essential for the long-term sustainable development of post-disaster recovery. This seminar presents the application of state-of-the-art machine learning algorithms in earthquake engineering, focusing on the performance-based seismic vulnerability and resilience assessment of civil systems, particularly bridges. This includes improving fragility curves, probabilistic seismic demand models, seismic resilience assessment, and analytical models of seismically-induced slope displacements. The overall outcome of this research empowers risk-informed mitigation strategies by developing physics-guided machine learning frameworks to tackle challenges towards a natural hazard resilient society. Zoom Meeting ID: 964 6812 4632; Passcode: 442246. We encourage everyone to attend and participate in person. For those attending in person, make sure you received a green status on your daily Mason COVID Health Check and please remember to for RSVP this event.

Speaker Bio

Farahnaz Soleimani is currently a Research Scientist at the Georgia Institute of Technology in the field of Structural Engineering and working in the research arm of the provost office. Prior to her current position, she was a post-doctoral scholar in the Machine Learning and Data Science Lab at Georgia Tech and Emory University. She received her BSc from Sharif University of Technology, and between 2013-2017 completed her MSc and PhD at Georgia Tech in Civil and Structural engineering, with a minor in Statistics. She also received an MEng degree in Civil engineering from Tufts University prior to joining Georgia Tech. Her research interest is mainly in the multi-hazard resilience assessment of structures and critical infrastructure systems. She develops computationally effective tools to better understand the seismic performance of structural systems by establishing predictive models and conducting sensitivity analysis. During her PhD study, in the Natural Hazards Mitigation Research Group at Georgia Tech, Dr. Soleimani developed an efficient approach to account for the irregularities existing in the bridge geometries towards developing a new generation of accurate fragility models for existing highway bridges in California. She has multiple leadership experiences such as serving as the Academic Relation Chair of the Society of Women in Engineering (SWE), and the Vice President of the Earthquake Engineering Research Institute (EERI). She has been the recipient of awards from Purdue Prospective Faculty program, SWE, and EERI, Georgia Tech Research and Innovative Conference, Student Government Association of Georgia Tech, and Doctoral Student Professional Development of the College of Engineering.