Can Quantum Computers Make Mass Transit Arrive on Time?

Trained as a structural engineer, he’d spent years designing bridges, railways, tall buildings, and infrastructure systems. The problems were physical and the objective was to design something that works better, lasts longer, and uses public money more efficiently.

Over time, as the excitement that came with seeing his first projects completed started to dim, he became increasingly fascinated with the computational side of his work. A decade earlier, during graduate research, he’d used high-performance computing (HPC) to explore complex fluid-structure interaction engineering problems, and as machine learning and data science gained momentum across the 2010s, he paid close attention and moved deeper into analytics.

The result was a career pivot. Though Assaad stayed at the same firm, he moved away from structural engineering to become a data scientist. Today, Assaad is a data science and analytics manager at the professional services firm STV, where he leads a team supporting architects, urban planners, transportation designers, and engineers. His work still focuses squarely on the physical world, but the interface is now data. That’s the background that got him thinking about quantum.

Learning the Foundations at a Quantum Epicenter

For Assaad, quantum seemed like the same sort of bet he’d made on HPC a decade earlier. “Twelve years ago, I didn’t know what problems I could solve with HPC, and then I found one, and I did my thesis on it,” he says. “I committed myself to leveraging state-of-the-art technology to solve complex problems. I feel like I’m in the same position today with quantum.” The question now is what problems this industry might have that are good fits for a quantum approach.

“I am constantly looking around and trying to imagine how these new technologies might apply,” he says. “How can I extract something out of these tools to benefit my colleagues, my work, and at the end of the day, how do I make our communities better?”

That question brought him to the University of Chicago’s Quantum Science, Networking, and Communications course, a program offered by UChicago’s Pritzker School of Molecular Engineering and managed by the Chicago Quantum Exchange. Across eight weeks, the course moves from linear algebra and the fundamentals of quantum information through Qiskit programming, entanglement, quantum key distribution, hardware and, finally, to a simulation of a multi-node quantum network using SeQUeNCe.

What intrigued Assaad was not that quantum promised immediate answers, but rather he saw the course as a way to get fully up-to-date on where the field stands and what its tools can do. He already knew about Chicago’s status as a quantum hub, but he also wanted to get insight into “where the money is going and what people are doing,” as he puts it. He wanted to see how quantum might matter for the kinds of large-scale optimization problems cities face every day.

The foundational modules during the first two weeks were the most valuable part for Assaad. He felt they moved him from intuition to real understanding. “It took me from ‘I think I know’ to actually knowing a lot and really understanding what the core concepts of quantum computing are,” he says.

The practical programming modules were useful too because they showed him how differently quantum problems are structured and how libraries like Qiskit make the programmer design circuits rather than write code in the usual sense. “The fact that you had to connect circuits and design circuits, it’s just completely different from how I code today,” he says. “I never really thought that you solve quantum problems through conducting circuits. I didn’t know that before the course.”

Some of the most useful learning happened between the sessions. The classmates Assaad connected with came from finance and defense, and the conversations revealed how differently each field approaches the same technology. What he valued most was seeing “how people with very different disciplines than mine are looking at quantum as a potential solution for their problems.”

Quantum for the City

If Assaad didn’t leave the course with a method he could apply immediately to a client project, he now sees where quantum might intersect with his work once the right use case, data, and access to quantum hardware come together. The program helped him see quantum making a difference in the large-scale optimization problems cities face every day—resource allocation, transportation planning, and questions about where limited tax dollars go—all challenges that typically involve massive datasets and an inconceivable number of variations on how scenarios might play out.

“What if we could explore many, many, many more of those scenarios?” Assaad asks, imagining a city with a major pothole problem. A conventional analysis would use the available data to recommend where repairs should be prioritized. A quantum-assisted approach could weigh each repair option against traffic patterns, transit reliability, emergency response times, planned construction, and even the underlying condition of the pavement all at once, and from there help officials decide where the next dollar would do the most good.

Assaad notes how the same logic applies to transit. “If I want to simulate a bus network running for a whole year, I can’t do that today with conventional machines,” he says. His point is that quantum could let planners model an entire transit system as one interconnected problem rather than a series of approximations.

“It would be possible to test how a schedule change on one line goes across transfers, dwell times, and rider patterns across the whole network for every season of the year.”

The stakes are high for Assaad, whose work has physical consequences, since a better model means more than just a better route or a better bridge or a more reliable commute. It means a better life in the city. “I want to be the person who was able to say, ‘We solved the inefficiencies in your transportation and infrastructure markets with this novel methodology.’”

For the time being, he’s waiting for the right client problem to show up on his desk. The course gave him the understanding to recognize it when it arrives. And if the infrastructure isn’t quite there yet, the conditions are converging fast, and so when his industry is ready, Assaad will already be waiting.