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Nguyen Bui grew up tending his family’s fields in Vietnam. Now, he’s exploring the potential of AI in medicine

Story by Misty Bouse, photos by Ric Getter and by Nguyen Bui.

91���� international student Nguyen Bui grew up helping his parents tend coffee, pepper and fruit crops. Today, the computer science student is contributing to international research that could help computers better analyze microscope images used in cancer research.

Bui is an equal contributor and co-author of a research paper examining a challenging problem in medical imaging: helping computers more accurately identify different structures in tissue samples.

The paper, “CoDiR: Confidence-Guided Diffusion Refinement for Semi-Supervised Histopathology Segmentation,” was accepted to the 2026 MICCAI COMPAYL Workshop in Strasbourg, France. Bui is listed with PCC as his institutional affiliation, putting the college’s name alongside those of researchers from other institutions involved in the project.

“Having an undergraduate student publish research at an international conference while completing lower-division coursework is an outstanding achievement,” said PCC Program Dean of Computing and Engineering Gayathri (GD) Iyer. “It highlights the incredible potential of our students and demonstrates that the foundational education provided 91����, along with the students’ motivation, enables them to engage with high-level academic research.”

She added, “Having additional avenues, such as research opportunities, hands-on projects, and practical applications of emerging technologies, allows students to explore their interests early and push their limits.”

For Bui, the opportunity combines a longtime love of mathematics with his desire to create something useful.

“I’ve had a passion for mathematics since I was young, along with a natural curiosity and love for creating things,” he said. “I chose computer science because I wanted to build something meaningful with that foundation.”

Making microscope images easier to read

Pathologists study tissue under microscopes to look for signs of disease. Researchers are also developing computer programs that can help identify and outline important structures within those tissue images.

Think of it somewhat like asking a computer to look at a complicated picture and draw a careful line around each object. That becomes especially difficult when parts of the picture look alike or when only a limited number of examples have been labeled by experts.

The research team developed a method called Confidence-Guided Diffusion Refinement, or CoDiR. In simple terms, it allows the computer to spend more effort double-checking parts of an image it is less certain about instead of treating every part of the image the same way.

Researchers tested the method on established collections of tissue images and reported that it performed as well as or better than another leading method on most of the measurements they examined.

The work remains research rather than a cancer diagnostic tool, but improving the way computers distinguish structures in medical images could eventually help researchers and health professionals analyze tissue more accurately.

“I wanted to challenge myself in a research environment and see what I could contribute, especially by applying AI to health care, a field where I feel this technology can make a real difference,” Bui said.

Lessons from the farm

Long before Bui worked with computer code or medical images, he learned about persistence from his parents. His family grows coffee, pepper, durian, passion fruit and other crops, and Bui often helped with the work while growing up.

“They taught me the value of hard work and dedication simply by living it every day,” he said. “As a child, I was often ‘recruited,’ in a fun way, to work alongside them, and through that I came to understand just how demanding that work truly is.”

Pursuing an education abroad required his family to make its own investment in his future. Bui describes it as “placing a bet,” supported by the crops his parents worked so hard to produce.

“Knowing that, I couldn’t afford to back down,” he said. “My parents have always been my driving force, pushing me to move forward every single day.”

That drive has taken Bui from working beside his parents in agricultural fields to contributing to research at the intersection of computer science and medicine. For him, the connection is straightforward: Use what he has learned to solve difficult problems and make his family’s investment count.

“The math and computer science groundwork I built through my coursework 91����’s Southeast Campus gave me the confidence and skills to take on this kind of research,” he said.

He took CS161B and CS162, building a strong core programming foundation that empowered him to pursue complex, independent research projects alongside his studies. According to Iyer, students who pursue a computer science path are prepared to tackle complex, real-world problems in cutting-edge areas like artificial intelligence, machine learning, and computer vision.

Their work, such as Nguyen’s research in histopathology segmentation, has direct applications in fields like medical imaging and healthcare technology, driving meaningful technical and societal advancements.

“Nguyen’s success is a reflection of his own drive, dedication, and independent research initiative,” said Iyer. “We are extremely proud of his hard work and initiative.”

Bui also credits support from a PCC Foundation Franklin High School Class of ’56 Endowed Scholarship for the 2026–2027 academic year for helping him to further his studies.

“As an international student, this scholarship meant a lot to me,” said Bui, who is a member of Phi Theta Kappa Honor Society. “It helped ease the financial burden of tuition and reduced a lot of the pressure I was carrying as I balanced my studies far from home.”

For more information, visit the PCC Computer Science program.