Jianfeng Zheng

By Stephen Greenwell

While numerous technical advancements have been made in the fields of medicine and materials, they ultimately can’t be implemented without practical, non-invasive methods. Jianfeng Zheng, an assistant professor in the Electrical and Computer Engineering Department at the Cullen College of Engineering, is using electromagnetics (EM) to make these advances possible.

“The complex environments I work with most often are the human body and underground (subsurface) structures. I study how electromagnetic fields interact with these complex materials,” he said.

Zheng always likes to provide practical examples of research he and his team are doing. Some recent projects include:

• Understanding how strong electromagnetic fields from medical equipment, especially MRI machines, interact with the human body and implantable medical devices.
• Developing stable data links in or on the human body to support patient-centered healthcare.
• Characterizing underground properties to help determine where petroleum may exist or whether CO₂ can be safely stored underground.
• Building physics-informed AI tools to combine elegant analytical and numerical methods with the power of artificial intelligence.

Exploring how large language models can be used to build EM “agents” that assist everyday users.

“Framing it this way helps people connect the research to real-world applications,” he said.

The campus environment at the University of Houston and the surrounding area, as well as the reputation of his colleagues in ECE, were what initially drew Zheng in.

“The university is home to several well-recognized experts in the EM field. Working with smart, kind, and hardworking colleagues is both exciting and motivating and it truly makes research enjoyable,” he said. “I also value the fact that whenever I have a question or a new idea, I can always find someone to discuss it with.”

Zheng noted that Houston was a great place to raise a family, between the warm climate, excellent food and convenient transportation networks. This is also likely why industry has flourished in the area as well.

“Houston offers tremendous industry opportunities in areas such as medicine, geophysical exploration, wireless communications and sensing,” he said. “Collaborating with people on the front lines and using our expertise to benefit society is one of the most exciting things you can do in your career. To me, there is no reason not to pursue that.”

When it comes to his development as a professor, a researcher and a person, Zheng pointed to different people from each phase of his life.

“My father, Chengye Zheng, worked as a small contractor, and he never did anything on science and research. But he has always deeply respected scientists and mathematicians,” Zheng said. “He shaped my early understanding of how mathematics and science benefit society and gave me my initial curiosity about science.”

In academia, Zheng has had significant influences at before UH and now that he’s at Cullen.

“I have to mention Professor Jianhua Lu, with whom I worked closely for several years at Tsinghua University in Beijing. Although he was not formally my supervisor, his leadership had a strong influence on me. He taught me how to dream big, and more importantly, how to turn big dreams into feasible research topics and concrete projects.”

“At UH, from Professor Ji Chen I have learned how to respond quickly, work hard and be fearless. He emphasized the importance of taking action, not being afraid to make mistakes and learning through doing, which helped me, who is usually overthinking, a lot.”

From a research perspective, like many others Zheng sees the promise in AI beyond trend-chasing. He calls its potential transforming for the way research is done.

“In my work, I use AI in two main ways. First, I apply large language models to create intelligent agents that can assist healthcare providers,” he said. “These users may not have deep EM knowledge, yet they must deal with complex issues related to electromagnetic interactions with medical implants.

“Second, I use physics-informed neural networks to solve complex and unstable problems. For systems where our physical understanding is incomplete, large data sets and reference models can be extremely valuable.”

“What excites me most is the feeling that I am helping improve the reasoning capabilities of AI itself, integrating human intelligence, which built our elegant scientific frameworks, with artificial intelligence, which is powerful and full of promise. Being able to work in such a disruptive and fast-moving area is something I find truly rewarding and enjoying.”