Biography

Madeleine Flint is a Postdoctoral Scholar in the Department of Environmental Earth System Science at Stanford University. Through a project funded by the Woods Institute for the Environment, Dr. Flint studies the potential impacts of regional-scale climate change on built infrastructure performance. This research is undertaken in collaboration with her postdoctoral advisor, Professor Noah Diffenbaugh, and with three faculty members of the Department of Civil and Environmental Engineering.

Climate change is expected to increase the risk of bridge failures during floods, and Dr. Flint’s research quantifies the changing risk and the resulting negative economic, environmental, and social impacts. In order to robustly characterize the risk and impacts, Dr. Flint integrates data and models from the multiple disciplines, including climate science, hydrology, environmental fluid mechanics, structural analysis, and life-cycle assessment. Dr. Flint uses a probabilistic approach, which allows her to provide robust operational guidance for the protection of vulnerable bridges, as well as for the development of performance standards. At the policy level, Dr. Flint’s research suggests methods for optimally allocating funds for climate change adaptation.

Dr. Flint’s research interests in are informed by her doctoral work in Civil and Environmental Engineering at Stanford University, her time as a transportation engineer at Caltrans, and her undergraduate studies in the Department of Structural Engineering at the University of California San Diego. Her doctoral work was funded by a National Science Foundation Graduate Research Fellowship, the Gabilan Stanford Graduate Fellowship, and the Achievement Rewards for College Students (ARCS) Graduate Fellowship.

In August of 2015, Dr. Flint will continue to investigate infrastructure performance as an Assistant Professor of Structural Engineering and Mechanics in Virginia Tech’s Charles E. Via Department of Civil and Environmental Engineering. She plans to continue to apply probabilistic approaches to assessing climate risk and durability in the support of sustainable infrastructure design.