Strategic care for aging infrastructure: a research Q&A with Dr. Qindan Huang

With approximately 620,000 bridges, 4.1 million miles of public roadways and 3.3 million miles of pipeline, the United States' transportation infrastructure requires upwards of $350 billion each year for operation and maintenance, with some organizations reporting that these investments still fall short by trillions of dollars. Beyond cost, these systems cross through all communities and are vital to the safe transportation of goods, resources and people.

For Dr. Qindan Huang, professor of civil, construction and environmental engineering, these are the high stakes behind her research and teaching at Marquette. Huang's research focuses on structural reliability and risk assessment for infrastructure.

In a current research project supported by the Minnesota Department of Transportation, Huang has developed and will soon implement a data-driven model to predict bridge repair needs caused by road salt corrosion.

In another project supported by the Department of Transportation's Pipeline and Hazardous Materials Safety Administration, Huang is developing a new approach to assess corrosion-prevention systems in steel pipelines. This work will allow industry and government organizations to better predict corrosion growth and pipeline integrity and make effective corrosion management decisions for these pipelines.

Huang's research leadership has earned her the Opus College of Engineering's 2026 Researcher of the Year award. In a Q&A, she discusses the latest developments in her work and what she sees for the future of the field.

What trends are you seeing related to your field?

A major trend in both the United States and globally is the rapid aging of infrastructure systems. Much of the existing infrastructure, such as bridges, pipelines and dams, has reached or exceeded the average service life of 50 years. As a result, the focus is increasingly shifting from new construction to the management, inspection, repair and maintenance of aging assets.

This shift highlights the importance of data-driven decision-making. As the saying goes, "If you can't measure it, you can't manage it." There is a growing need for predictive models that accurately assess structural performance, quantify risk, and support more informed, cost-effective maintenance strategies.

More than just finding resources to maintain infrastructure, we need to develop a solid strategy for how to deploy those limited resources across so many high-need projects.

What changes could an average citizen expect to see in their communities as your field advances?

If we're successful, the average citizen can expect to see more reliable, resilient infrastructure in their daily lives. This includes systems that are better maintained, experience fewer unexpected failures, and have minimal service interruptions.

Behind the scenes, this improvement will be driven by the effective use of comprehensive data to inform management decisions. By leveraging predictive models and integrated data sources, infrastructure agencies can shift from reactive repairs to proactive maintenance - addressing issues before they become visible problems.

Ultimately, this means safer communities, more efficient use of public resources and greater confidence in the infrastructure people depend on every day.

What motivates you to lead this work?

I am motivated by the opportunity to develop practical solutions to complex engineering challenges that improve infrastructure safety and reliability. My work can help improve quality of life and safety across the country, so I see it as my opportunity to use my skills to serve others.

I am also driven by mentoring students and helping them build problem-solving skills, grow in confidence, and realize their potential. They will soon be working alongside me to serve communities, and it excites me to know how much they will be able to achieve in their careers when they leave my classroom.

As you look ahead, what are the problems, opportunities or new factors that will be at play in your area of research?

AI-assisted approaches are becoming increasingly central to engineering research. A key challenge and opportunity will be effectively integrating data-driven methods (such as AI) with physics-based principles. Successfully combining these approaches will enable more accurate predictions, better decision-making and more efficient solutions to complex engineering problems.

As with any engineering field, the opportunity presented by AI is balanced by the need to 'get it right,' which means accuracy, ethics and safety are our top priorities. When we are talking about bridges in our neighborhoods or pipelines across our land, the stakes are extremely high. That means the stakes are equally high in our classrooms, as the stewards of our infrastructure are just beginning their education right now.