AI Pioneer: Vietnam Tech University Top Graduate Publishes 3 International Papers on Medical AI

Nguyen Minh Hien, a top graduate from the University of Technology, Vietnam National University Hanoi, has achieved three international publications on AI applications in medical data analysis, earning him the title of "thủ khoa" (top graduate). With an impressive GPA of 3.93/4.0, Hien has focused on the interdisciplinary field of "Tin-Sinh học" (Bioinformatics), aiming to apply his knowledge to cancer research and precision medicine. Hailing from Bac Ninh province, Hien possessed a strong foundation in mathematics and informatics from his high school years, where he won national awards. Upon entering university to study Information Technology, his path took a significant turn in his second year when he joined a research group. It was then that he discovered the exciting intersection of IT and Biology. "Bioinformatics allows me to see how programming, algorithms, and artificial intelligence can support the analysis of complex biological data, especially in cancer research and precision medicine," Hien explained. "This is a timely research direction with significant development potential." In the early stages of his research, Hien encountered challenges due to the complexity of existing scientific papers and the lack of detailed implementation specifics, making it difficult to replicate experiments. He was assisted by his research group colleagues in understanding source code, implementing, and adjusting experiments related to breast cancer data analysis. Hien also delved deeper into algorithms, machine learning, and biomedical data analysis methods, supplementing his understanding through international literature and discussions with his instructors and senior group members. Hien views learning as a "long-term game," emphasizing the importance of resource allocation and strategic planning to tackle difficult problems. He broke down his academic and research goals into smaller objectives to manage pressure. He strategically completed most of his coursework within the first three years, then gained practical experience at a technology company to broaden his perspective on complex data such as medical images and proteins. He dedicated 20-30% of his time to research. By his fourth year, he had become a co-author of three international publications on the application of AI in analyzing cancer data. Two of these were published on IEEE Xplore, and one on Springer Nature, both reputable global scientific databases. These studies explored various types of patient biological data, including gene activity levels and DNA variations, to aid in cancer subtyping and the identification of relevant biomarkers. "These results can inform future research, contributing to more personalized diagnosis and treatment for patients in the future," Hien stated, detailing his role in literature review, data processing, running experiments, verifying results, and refining the experimental process. The three publications also formed the "backbone" of his graduation thesis on applying AI to construct evolutionary trees, a computational research approach that analyzes relationships between biological samples. "In vaccine research, it provides information on virus changes, helping scientists evaluate and update vaccine components when necessary," he described. Hien believes that conducting research requires students to read independently, experiment, document discrepancies, and adjust their methods with each iteration. This, he says, is his favorite but also most pressure-inducing task. "AI experiments on biomedical data require significant computational resources, so I had to learn to flexibly use platforms with GPUs, optimize source code, and manage experimental runtime," Hien shared. He realized that simply replicating a research paper wouldn't yield results; understanding the problem, verifying data, checking source code, and conducting systematic experiments were crucial. Dr. Hoang Thi Diep, a lecturer in the Faculty of Information Technology and Hien's research and thesis supervisor, praised his special passion for life sciences and his seamless collaboration with his research group. "Hien has a strong algorithmic foundation, a high capacity for self-learning, and is very persistent in experimental work," she commented. Hien plans to pursue a Master's degree to further cultivate his academic knowledge in the coming years. "The most valuable thing for me is not just having international publications, but learning how to conduct research within a serious team: reading independently, experimenting, knowing when to ask the right questions, and recognizing the contributions of my collaborators," Hien concluded.