Anne Kiremidjian is the C.L. Peck, Class of 1906 Professor in the School of Engineering, Civil and Environmental Engineering, at Stanford University. In addition, she was Co-Director and then Director of The John A. Blume Earthquake Engineering Research Center at Stanford for 15 years. Dr. Kiremidjian’s research has focused on earthquake hazard and risk assessment methods and structural health monitoring using advanced sensors and algorithms. Within the earthquake hazard and risk assessment area, she has focused on developing methods for resilient urban systems, including transportation, power, water/sewer and communications systems. The majority of these models can be readily extended to other extreme events such as hurricanes, tornadoes, climate change and blasts. A second area of research addresses the design and implementation of wireless sensor networks for monitoring of structures under every-day loading conditions, and the development of robust and computationally efficient algorithms for structural damage diagnosis following extreme events that can be embedded in wireless sensing units. The damage algorithms utilize modern data science, machine learning and artificial intelligence methods. Dr. Kiremidjian has earned numerous awards and honors including an Honorary Membership in the Earthquake Engineering Research Institute, a Distinguished Membership in the American Society of Civil Engineers, the John Fritz Medal from the American Association of Engineering Societies, and the Thomas Egleston Medal for distinguished engineering achievement from the Columbia University School of Engineering. Dr. Kiremidjian holds bachelor’s degrees in physics and civil engineering from Queens College of the City University of New York and Columbia University, respectively, as well as a master’s and doctorate in structural engineering from Stanford. She was elected to membership in the National Academy of Engineering in 2021 in recognition of her research and dissemination of probabilistic seismic hazard methods and mentoring.
Title: Sustainable, Smart, and Resilient Infrastructure
Abstract: Incorporating smart and resilient components is critical for achieving sustainable infrastructure systems. Smart systems provide the tools for managing and operating the systems in an optimal way, thus reducing environmental effects and life-cycle costs, and increasing efficiency in functionality. Resilience modeling provides the tools for pre-catastrophic event planning and post disaster efficient response. Pre-event recovery information leads to robust design, upgrade and rehabilitation decisions that reduce the recovery time, the environmental consequences and increase the functionality of a community. Pre-event planning also increases the post-event disaster response efficiency resulting in reduced casualties, reconstruction time and return to normal operations. The smart system metastructure and resilience modeling paradigms are introduced with simple illustrative examples.