Across infrastructure – from transportation and buildings to energy, water and environmental systems – research plays a central role in how owners and project teams manage risk, prioritize investments and make critical decisions about asset performance. Yet even technically sound research doesn’t always translate cleanly into practice, leaving decision-makers to bridge the gap on their own.
Peer review sits at the center of this challenge – not just as a quality filter, but as a checkpoint for how effectively research can support real-world decisions. Nowhere is this more evident than in practitioner-facing journals, where academic rigor must align with the realities of project delivery.
In this Q&A, Anjan Ramesh Babu, Ph.D., PE, senior structural engineer at STV and a handling editor for Transportation Research Record, reflects on what distinguishes research that not only succeeds in peer review but also improves engineering practice. Drawing on his editorial vantage point, he discusses the clarity of assumptions, repeatability and common points where research-to-practice translation breaks down, along with practical ways authors and project teams can avoid those pitfalls.
1. From your vantage point as a handling editor, what distinguishes research that becomes actionable from research that stays theoretical?
As both a practicing bridge engineer and a Handling Editor for the Transportation Research Record, I see the most valuable research come from real-world problems – issues that engineers or owners are actually facing. The strongest studies don’t just prove something works; they spell out where it works, where it doesn’t and why that matters for someone making real project decisions.
The studies that stand out clearly connect findings to the decisions engineers and owners have to make – whether evaluating an aging bridge, prioritizing investments or managing risk across an asset portfolio.
At the end of the day, research only delivers value when practitioners can apply it with confidence on their own projects. That confidence often comes from how well research anticipates real-world conditions and supports shared decision-making between engineers, owners and stakeholders.
2. What assumptions do authors most often leave implicit – and why does that derail real-world use?
One of the biggest hurdles is that researchers often assume their readers know what they know. They might leave out key information such as a method’s limits, the conditions it was designed for or situations where it just doesn’t fit. For owners or design teams, those details matter because no two projects are exactly alike. Being clear and upfront about assumptions helps engineers determine whether a piece of research fits their project or requires them to use their own judgment.
3. Repeatability matters in peer review, but field conditions are never identical. What does “repeatable enough” look like in practice?
No two infrastructure projects are the same, so repeatability doesn’t mean getting identical results every time. What matters is having a method that is clear, reliable and delivers consistent results in similar situations. Good research recognizes that engineers must always factor in the unique details of each site. The real goal is to offer a framework that works across a variety of real-world projects and not just in perfect lab conditions.
4. Where does translation from research to project decisions most often break down, and how can teams avoid that?
The challenge is rarely the quality of the research – it’s translating it into decisions teams can act on. Too often, research papers explain what was discovered, but don’t focus enough time on how those discoveries should shape actual project decisions, specs or delivery. The projects that succeed treat this as a shared responsibility – bringing researchers, owners and engineers together early and keeping the work focused on real-world needs. When that alignment happens, research is far more likely to translate into decisions that improve outcomes on the ground.
5. If you could change one thing about how research is written to better serve owners and project teams across infrastructure markets, what would it be?
I would ask every research project to include a straightforward “what this means in practice” section. Owners and project teams do not just want technical results; they need to know how those findings affect real decisions, project risks, costs, or long-term performance. Even a quick summary of practical takeaways can make great research more helpful for the people who have to deliver infrastructure.
6. What separates research that changes industry standards from research that simply gets published?
In my experience, research that changes industry standards tackles a real problem the industry is already facing. It combines strong technical work with practical validation and is transparent about its assumptions and limitations.
What also sets these studies apart is that they build confidence over time. Standards are rarely changed because of a single paper. More often, a body of research accumulates evidence through independent validation, field testing and successful application across multiple projects. The research that shapes standards earns the trust of owners and designers because it demonstrates value in practice, not just in theory.
7. How can owners determine whether new research is ready to apply to their projects?
Getting published is an important milestone, but it is only the beginning. Owners should ask several key questions: Has the research been independently validated? Has it been tested or applied beyond the original study? Are the limitations clearly documented? And does it align with the conditions of the project under consideration?
Research is ready for implementation when it provides engineers and owners with sufficient evidence to apply it with confidence – with a clear understanding of both the potential benefits and the risks in their specific project context.
8. Looking ahead, what do you think will define the next generation of infrastructure research?
I think the next generation of infrastructure research will be even more collaborative, data-driven and focused on getting results into practice. Tools like structural health monitoring, digital twins and AI are opening new ways to understand how infrastructure performs over time.
But it won’t just be about technology. Engineering judgment, experience and collaboration will remain essential in translating that data into decisions teams can trust. Ultimately, the most valuable research will combine better data with sound judgment – helping owners and engineers make more informed decisions that lead to safer, more resilient and cost-effective infrastructure.
