Program Overview

The Resilient Transportation Infrastructure Systems (R-TIS) program develops innovative solutions to improve the sustainability, equity, and resilience of transportation infrastructure systems for existing and emerging transportation modes. The program aims at developing new materials, structures, and management strategies that improve infrastructure durability, reduce environmental impact, preserve natural resources, and promote sustainable development to benefit all members of society, regardless of their socioeconomic status or physical abilities. R-TIS emphasizes the importance of integrating resilience considerations into transportation infrastructure systems to improve their ability to withstand and recover from natural disasters, climate change, and other disruptions.

The program draws on interdisciplinary expertise from fields such as civil engineering, industrial and management engineering, environmental science, and social sciences to advance the state of knowledge in transportation infrastructure design and system management and promote the adoption of best practices in the field. Through collaborative research, education, and outreach efforts, R-TIS aims to create more sustainable, equitable, and resilient transportation systems.

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R-TIS Program

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Mingyang Li, Ph.D.

Associate Professor, Industrial and Management Systems Engineering University of South Florida
Phone: 813-974-5579
Photo of Mingyang Li, Ph.D.


Mingyang Li, Ph.D., is an associate professor of Industrial and Management Systems Engineering at the University of South Florida. His primary research has focused on developing advanced statistical models and computational tools, integrated with domain knowledge, to improve system performance modeling, analysis, monitoring, diagnostics, prognostics, and decision-making. Specifically, he has developed Bayesian data fusion and parametric/nonparametric heterogeneity quantification methodologies for reliability modeling, failure prognosis, and maintenance optimization of complex deteriorating systems, such as aging critical infrastructures. He received his doctoral degree in Systems & Industrial Engineering and MS in statistics from the University of Arizona. He also received an MS in Mechanical & Industrial Engineering from the University of Iowa. Dr. Li is a member of INFORMS, IISE and ASQ. Learn more