In a landmark achievement for undergraduate research, Zhou Qi, student majoring in Intelligent Manufacturing Engineering(grade 2022) at the Shien-Ming Wu School of Intelligent Engineering, has published a research paper in the prestigious journal Nature Machine Intelligence. Co-first authored with Professor Dai Dong from the School of Electrical Engineering, this work marks the first time an undergraduate student has led a publication in a Nature family journal within the university.

This study proposes a universal framework called the Free Boundary Neural Operator (FBNO), which for the first time extends the applicable boundaries of neural operator methods from predefined fixed regions to complex, dynamically evolving regions with unknown initial conditions, thereby filling a long-standing research gap in the inability of neural operator frameworks to directly solve free boundary problems (FBPs).

As a core member of the research team, Zhou Qi demonstrated solid scientific expertise. Throughout the entire research cycle, he was deeply involved, primarily responsible for proposing and refining methodological frameworks, conducting numerical simulations, and drafting academic papers. Through comprehensive research experience, he systematically went through the entire process—from identifying scientific questions and implementing research plans to producing scholarly outcomes—developing robust research thinking skills and capabilities.

Zhou attributed his success to the school’s educational philosophy, which emphasizes systematic thinking and innovation. The undergraduate curriculum offers extensive breadth and remarkable flexibility, Zhou noted. It provides ample space for independent exploration and serves as a critical foundation for conducting interdisciplinary research.