Brett A. Story, Ph.D.
Assistant Professor, Southern Methodist University
Many critical civil engineering infrastructure components are approaching or have exceeded their intended design lives. Efforts to streamline efficiency in transportation and energy have increased demands on these aging structures. This talk discusses the dilemmas of managing civil engineering infrastructure and outlines solutions that integrate data from multiple sources with machine learning towards enhanced structural monitoring, evaluation, and design. An interdisciplinary, machine learning framework is presented that fuses quantitative and qualitative data streams in an effort to increase efficiency and accuracy of automated and semi-automated structural evaluation and design. Highlights from the application of such frameworks to bridge infrastructure are detailed.
Bio: Dr. Brett Story received his B.S., M.S., and Ph.D. from Texas A&M University. Dr. Story joined the Department of Civil and Environmental Engineering in the Bobby B. Lyle School of Engineering at Southern Methodist University in 2013. His area of expertise is broadly structural engineering with an emphasis on innovative integration of mechanics, instrumentation, and machine learning to develop efficient solutions for monitoring and design of civil engineering infrastructure. Dr. Story’s work has been funded by NSF, local government, and industry.