From helping students find their footing in daunting computing concepts to making sprawling software systems more reliable, Professor Hua Ming has built a career around a single conviction: complexity is something people can learn to navigate. That belief has traveled with him since his first application for an academic position, where he wrote a sentence he still stands behind: “Anyone who wants can learn computing.”

“It has stayed with me ever since,” he says. Years of teaching, research and academic leadership later, it still shapes every conversation he has with a student.

Now a professor in Grand Valley State University’s College of Computing, Ming wants students to discover that complexity — whether a mathematical theory, a massive codebase or an unfamiliar area of research — is a door rather than a wall. “There is nothing more rewarding than watching a student’s ‘aha!’ moment,” he says. “My goal in the classroom is to show that even the most abstract STEM subjects can be made accessible to our students.”

Rather than opening with dense formulas, Ming helps students build intuitive mental models of what is happening beneath the mathematics. The point is not to strip out the hard material but to give students a way into it. It is a philosophy that fits naturally in a college that has made “AI for Everyone” a guiding commitment: the conviction that computing belongs to every student, not only those who arrive already fluent in it.

Building Software We Can Understand and Trust

The same instinct drives Ming’s research. Modern software systems contain enormous amounts of interconnected code, and as they grow, understanding, maintaining and trusting them becomes steadily harder. Ming draws on machine learning, formal logic, programming languages, software verification and testing, and complex networks to find better ways to keep that complexity in check.

“The goal of my research is both ambitious and practical: making the growing complexity of modern software systems easier to understand, manage and trust."

One current project tackles a problem almost every smartphone user will recognize: an app that suddenly crashes. “Every Android user knows the frustration of an app suddenly ‘force closing,’” Ming says. “As a researcher, I see these crashes as more than just an annoyance. They represent a fundamental gap in how we build complex software in the real world.”

Many of those crashes trace back to runtime exceptions — errors that surface only while the software is running — and even expert developers introduce them as systems grow. With support from a Google Academic Research Award, Ming and his team are exploring how to shift the burden of catching those errors away from individual programmers and toward the tools used to build and test software.

The ambition mirrors the philosophy behind much of his work: rather than expecting people to navigate ever-more-complicated systems flawlessly, make the systems themselves more understandable and reliable. That principle also sits at the center of the college’s work on trustworthy AI. As Director of Research for the West Michigan Trustworthy AI Consortium, Ming brings the same rigor to a question the region’s employers and communities are asking with growing urgency: how do we know the intelligent systems we depend on will behave as intended?

At GVSU, he also hopes to carry his research into new territory, including public health and cybersecurity — exactly the kind of cross-disciplinary reach the college’s Computing+X programs are designed to encourage.

Curiosity Over Experience

Throughout his career, Ming has worked with undergraduate and graduate researchers on projects ranging from honors theses to industry collaborations. Students gain experience from that work, but Ming is quick to point out that the learning runs both ways. “I have always learned from my students,” he says. “Each one of them brought in a unique combination of sharpness, curiosity and willingness to win.”

For students wondering whether they have enough background to join a research project, Ming’s answer is that experience is rarely what matters most. He looks for a willingness to experiment — to try a new tool, weigh a different approach or adopt a new way of thinking. “In a rapidly changing tech world, that counts more than already acquired skills or experiences,” he says.

It is the same message he delivers in the classroom, and it echoes the college’s Shipyard model of learning by building: students don’t need to arrive as experts. They need a real project, a willing mentor and the curiosity to begin.

Finding a New Home at GVSU

Ming’s path to GVSU began, fittingly, with a conversation at another university. Meeting with some of that institution’s top students, he asked why they had chosen their school and their computing major. One student said her mother had wanted her to attend a school close to home. Ming followed up with a simple question: where had she wanted to go after high school?

Her answer: GVSU. Her reason was just as simple. “Because it is fun!”

“I think she hit the nail on the head,” Ming says. Beyond being roughly 20 minutes from Lake Michigan — a proximity he is particularly enthusiastic about — he was drawn to GVSU’s students, campus and culture. “It is indeed a fun place to learn, to grow and to accomplish.”

As he begins this next chapter, his aspirations extend beyond courses taught or papers published. Several years from now, he hopes colleagues and students will see him as a team player, an encouraging colleague and, in his words, a “super communicator” whom faculty, staff and students enjoy talking with.

Precision and Possibility

Away from computers and code, Ming turns to another complex pursuit: music. He plays violin, his wife plays piano, and the two enjoy playing together, including works by Bach and his arrangement of Marcello’s Adagio (BWV 974).

For Ming, music is an intriguing counterpart to his professional life. His research may deal in algorithms, logic and machines, but music has its own blend of complexity, creativity and rigor. “It’s a reminder that even in a world of discrete bits and bytes, there is always room for the fluid, human resonance of a well-placed vibrato,” he says.

That balance between precision and possibility is one he intends to keep exploring. “Through my research, teaching and creative pursuits, I hope to continue exploring the intersection of precision and possibility at GVSU,” Ming says, “working with colleagues and students to make complex technologies more reliable and help students discover their own confidence and passion in mastering them.”