From village roads to radiology, Auburn mathematician finds the patterns behind life

As a child in southeastern Nigeria, Chinedu Anthony Eleh did not know he was thinking like a mathematician.

He only knew the buses.

In his village, market days followed a four-day cycle. Before buses and taxis passed through the streets to pick up passengers, Eleh could identify certain drivers by sound alone.

“When my mother was planning to go to market, she would say, ‘Let me know when this person passes,’” Eleh said. “Just by listening to the sound, I would know. I would say, ‘Mommy, this driver is here.’”

Later, while staying with his brother, who owned a shop in northern Nigeria, Eleh found another outlet for pattern recognition: checkers.

“I would be in the shop, and people would line up. I would beat them one by one,” he said. “All of that was a lot of calculations and strategies, but I still didn’t understand what all that meant until I was enrolled in school. Then I realized, ‘Oh, this is actually math.’”

That realization eventually led Eleh to Auburn University’s College of Sciences and Mathematics, where he earned a PhD in applied mathematics through the Department of Mathematics and Statistics and a second master’s degree in data science. Now, he is preparing for a postdoctoral position in the Translational Ultrasound Lab in the UC San Diego Department of Radiology, where he will work on an NIH-funded project using real-time 3D ultrasound imaging to study cancer.

The project brings together ultrasound technology, mathematics and machine learning to better understand the blood vessel systems that help tumors grow and change. Working with researchers at Stanford University, the Hamburg University of Technology and industry partners, Eleh will help develop tools that connect ultrasound imaging patterns to information doctors can use in cancer care.

For Eleh, the work builds on the kind of math he studied at Auburn: using computers to understand change.

“Differential equations model rates of change,” Eleh said. “Life is full of rates everywhere.”

Speaking has a rate. Movement has a rate. Medical data have rates. By studying those changes, researchers can begin to model the systems behind them.

“You use data to learn maps and functions that can make predictions,” Eleh said.

In the UC San Diego project, Eleh will apply that idea to ultrasound data, helping develop mathematical tools that can turn complex imaging patterns into information doctors can use in oncology and patient care.

The work also reflects the broader mission of the lab — increasing ultrasound’s clinical impact as a bedside, inexpensive, radiation-free and noninvasive imaging tool. For Eleh, that accessibility matters.

“Many people suffer from cancer without knowing, simply because the care or the diagnosis is too expensive,” Eleh said. “What this is all about is making bedside science cheaper and more accessible.”

Eleh grew up in southeastern Nigeria, attended secondary school in the northern part of the country and later earned degrees from the University of Nigeria, Nsukka, and the African University of Science and Technology in Abuja. He first learned about Auburn through academic connections, then found an adviser in Associate Professor Hans-Warner van Wyk, who encouraged him to pursue questions that crossed traditional boundaries among numerical analysis, statistics and machine learning.

“I’m so proud of everything Auburn offered me,” Eleh said. “I’m not sure I would have gotten the same treatment from any other place.”

Auburn also prepared him as a teacher. Since 2019, Eleh has taught or assisted with a wide range of courses and served as a mathematics tutor and mentor through COSAM’s Office of Academic Engagement, Innovation and Opportunity  in addition to teaching almost all undergraduate mathematics and statistics courses in the department of mathematics and statistics.

“That’s an experience you don’t get in many other places,” Eleh said. “It prepared me very well for future teaching.”

For Eleh, the connection from village roads to radiology is not as far apart as it might seem. The child who once recognized buses by sound was already listening for patterns. The teenager beating challengers at checkers was already calculating strategy.

“I like to dissect things,” Eleh said. “If I’m in a room full of people, I will keep asking, ‘Why is this? Why is that? Eventually, the Whys would always lead to other pertinent questions, like the ‘when,’ the ‘what,’ the ‘where’ and finally ‘by whom, even in situations when nobody cared about these questions.”

Now, as he moves into radiology and cancer-focused research, that instinct continues to guide him — asking why, finding patterns and using mathematics to understand what is happening beneath the surface.