As artificial intelligence (AI) tools become increasingly integrated into contemporary technologies and workflows, they become similarly integral to a comprehensive engineering education and preparation for the global workforce. At the Cullen College of Engineering, that work is not a collection of isolated experiments. It is a college-wide effort, carried out across departments, to preserve rigorous technical and disciplinary foundations; to teach students to understand, evaluate and apply AI; to use AI thoughtfully as a learning tool; and to advance research that expands what the technology can do.
In line with the Cullen College of Engineering’s mission to serve Texas and beyond by educating engineers to be leaders, advancing shared knowledge through research and scholarship, and facilitating the transfer of new technology to Texas industries, the thoughtful, considered incorporation of AI into the college’s curriculum is critical.
Though the typical image of “AI” is often one of generative language models like ChatGPT, there are far more diverse and specialized applications of artificial intelligence tools to engineering topics than language generation. Artificial intelligence tools have the potential to simplify and expedite specific tasks, especially those involving image analysis, in ways that not only increase productivity but enhance accuracy and efficacy.
Because AI capabilities and their impact on engineering work are changing so quickly, the college’s strategy cannot be static. Through college- and department-level advisory structures, alumni engagement and direct dialogue with employers, Cullen has built continuous feedback into its related planning. This allows the college-wide effort of enhancing students’ AI fluency, including disciple-dependent curricula and student experiences, to evolve in concert with the contemporary, AI-augmented workforce.
“Our goal at the UH Cullen College of Engineering is to ensure our students are industry-ready for an AI-augmented workforce upon graduation,” says Dean Pradeep Sharma. “However, we are also keenly aware of the perils of over-reliance on these tools. We are committed to integrating AI thoughtfully, ensuring that our students retain their rigorous critical thinking skills and use AI to accelerate innovation and creativity, rather than outsourcing it.”
AI in Research
In recent years, Cullen researchers have used deep learning to automate the mapping of glacier grounding lines in Antarctica, AI models to assist radiologists in disease diagnoses, edge-graph aware neural networks and large multimodal models to help better predict the factors that drive pandemic spread, and more. UH also offers a Master of Science and a Graduate Certificate in Engineering Data Science and AI. Together, these examples show the breadth of AI-related research and education at UH and the importance of preparing students to understand and apply the technology in a rapidly changing skills market.
AI as a Learning Tool
Within that broader framework, Civil and Environmental Engineering’s Kaspar J. William Assistant Professor Mim Rahimi sees AI as a “useful educational tool when it is implemented carefully;” he cautions that it should not replace the learning process, but can support it in the right circumstances.
“I think of AI as a 24/7 digital learning assistant, but only if it is designed with the right boundaries, sources, and pedagogical structure,” Rahimi says. “I try to engage with these tools first as a user and then as an instructor. Before suggesting any AI tool to students, I want to understand what it can do well, where it fails and what risks it creates. That includes accuracy, hallucination, privacy, data use and whether the tool supports learning or simply bypasses it. My goal is not to promote AI uncritically, but to help students use it with judgment, transparency and accountability.”
Rahimi has also written about the responsible use of AI in higher education in a Nature World View article, emphasizing the need to integrate these rapidly evolving tools in ways that strengthen, rather than replace, the learning process.
Just as important as its deliberate implementation, however, can be its deliberate exclusion.
“Instructors need to be clear about how AI should and should not be used, ideally directly in the syllabus. The message should be that AI is a learning support tool, not a substitute for learning. It should not bypass the cognitive work that education is meant to build, such as reasoning, problem solving, writing, calculation and critical thinking,” he adds. “Used well, AI can make students more engaged and better supported. Meanwhile, it can weaken the very skills we want them to develop if used poorly.”
Rahimi also notes that today’s students “are not necessarily anti-AI.”
“In many cases, they are using these tools already. But use does not always mean trust. I think that distinction is important. Students want to know whether AI will help them learn or simply replace parts of the learning process. They also want clarity about what is allowed, what is ethical, and what skills they still need to build for their future careers. So, for me, the key is not to push AI or reject it. The key is to teach students how to evaluate it, use it responsibly, and understand both its benefits and its limits,” Rahimi says.
Using AI ethically also requires sufficient technical understanding of how these models work, where bias and error can enter and how their outputs should be validated. Engineering education has an important role to play in building that technical understanding, so responsible use is grounded in knowledgeable analysis and judgementrather than in static rules. To put this philosophy into practice in a systematic, pedagogically grounded and instructor-controlled way, Rahimi developed AskNaro, a digital AI teaching assistant that will be implemented in his Environmental Chemistry course in Fall 2026.
AskNaro is designed to operate within instructor-defined boundaries and course materials, giving students access to an AI learning assistant while allowing the instructor to maintain control over its scope and use. The platform is also designed so that other instructors can create their own course-specific digital AI teaching assistants, with plans to extend its use to additional courses in the near future.
AI as an Engineering Skill
Using AI as a learning aid is only one part of Cullen’s approach. Students must also develop AI fluency as an engineering skill, and faculty development is part of that college-wide effort. More than 130 Cullen College faculty attended a recent, well-received “AI Workshop for Pedagogy” co-led by Professor of Practice Alex Landon. Landon has also created a document for her classes and students that specifically outlines how she uses AI in the classroom and her expectations around its use. It’s now part of her core syllabi.
In Landon’s honors sections of Engineering 1100 — the introduction to engineering course that all engineering majors will take — there are four major, graded projects, and one of these projects is now fully AI-focused. Students must use artificial intelligence alongside design thinking to satisfy the grading requirements for this project — and for good reason.
“The goal is for students to, one, have guided space in class to let them know what tools are currently available and what the best ways to use them are, and two, to get hands-on building experience. I structured it this way because I think, increasingly, the consensus in how to teach students about AI is that there needs to be technical concept conveyance, like lectures, but a huge part of the learning comes from doing hands-on exercises and evaluating firsthand where a tool excels or falls flat, all of which will change as the models themselves continue to evolve,” says Landon.
Though some students remain opposed to the use of AI tools — Landon estimates that it’s around 10 percent of her students so far — her primary goal is to ensure that her students are prepared to be excellent and ethical engineers, and having hands-on knowledge of these tools is necessary to meet those goals in today’s world.
“I have felt comfortable reminding those students that whenever AI is optional, they do not have to use it. That is a personal choice. But for one of our four projects they are pushed to explore the tools; AI is a key technology that they’ll need to know to stay competitive and cutting-edge. It is helpful that all the students have access to paid accounts for Microsoft Copilot and Google Gemini through UH and we use those tools for the assignment,” she adds. “One of our jobs as educators in teaching students about AI is to help them develop intuition for when it would be irresponsible to use AI tools and when it would be irresponsible not to use AI tools, all of which is ever-evolving as the tools themselves evolve.”
A College-Wide Baseline
These efforts are not isolated faculty experiments; they are examples of a broader college-wide trajectory toward producing graduates whose technical competence and AI proficiency are mutually reinforcing. Above all, the Cullen College of Engineering and its faculty continue to “focus on a curriculum that strikes a delicate balance between technological fluency, ethical awareness and strict disciplinary relevance,” says Sharma. “Just as the calculator didn’t replace the need to understand math, AI tools shouldn’t replace the core elements of our engineering instruction.”
Still, he says, the AI genie is “out of the proverbial lamp… and it’s not going back!” On this account, the Cullen College of Engineering will continue using feedback from alumni and industry leaders, combined with expertise from its own researchers, to refine its approach to AI as both a tool and an opportunity.