Professor Hyoseon Yang at the Department of Mathematics has been named a 2025 POSCO Science Fellow by the POSCO TJ Park Foundation. This fellowship recognizes outstanding early-career researchers (ECRs) in basic and applied sciences, providing a research fund of 100 million KRW over two years. In addition to financial support, fellows gain access to resources and programs designed to foster their growth as global leaders in science. Professor Yang was selected for her innovative and impactful research on “Approximation Methods for Large-Scale Multidimensional Data,” a project poised to push the boundaries of data analysis and computational mathematics

Breaking New Ground in Data Approximation
Professor Yang’s research focuses on pioneering new techniques for approximating and analyzing large-scale, multidimensional data. Her work seeks to address complex challenges in applied mathematics and computational science by developing mathematical models that simplify irregular data patterns and uncover hidden trends.

As machine learning technologies advance and the demand for big data processing continues to grow, the importance of robust data approximation methods has never been greater. Yet, traditional techniques often fall short, facing limitations in computational speed, accuracy, and memory efficiency. “Existing approximation methods struggle with both precision and computational efficiency,” explained Professor Yang. She emphasized the need for innovative approaches tailored to the structure and characteristics of specific datasets, calling for solutions that transcend the boundaries of conventional theories.

In her previous work, Professor Yang developed high-order approximation techniques tailored for irregular data on uniform grids. Building on this foundation, she is now addressing the challenges posed by real-world data, which often exhibit irregularities or concentrated clusters in specific regions. Her current research integrates theoretical advancements—emphasizing stability, error minimization, and convergence—with the practical development of algorithms for applied applications. This work seeks to enhance analytical accuracy while streamlining computational efficiency.

Professor Yang’s contributions extend beyond theory, offering transformative applications in a variety of fields. For instance, her methods can be used in medical imaging to reduce noise caused by patient movement during MRI scans, producing sharper and more consistent results. Her techniques also hold promise in areas such as machine learning, big data analytics, and nuclear fusion technology. “These new approximation methods have significant potential for multidimensional and irregular datasets,” she said, underscoring their broad applicability.

A Key Role in Advancing Nuclear Fusion
One of the most exciting aspects of Professor Yang’s work is its potential for nuclear fusion technology, one of the holy grails in modern science. “High-precision modeling of plasma behavior, which is a critical foundation of nuclear fusion research, requires accurate solution of fluid dynamic equations for plasma,” she explained. By leveraging sparse grid-based approximation techniques, her research could lead to more accurate solutions for high-dimensional partial differential equations, ultimately advancing the development of nuclear fusion technology and creation of an artificial sun by ITER (International Thermonuclear Experimental Reactor), of which Korea is one of the members.

This fellowship opens the door to groundbreaking advancements in both theory and application, solidifying Professor Yang’s role as a trailblazer in her field. With the support of the POSCO Science Fellowship, she plans to deepen her exploration of foundational scientific research. Reflecting on the honor, she said: “As an early-career researcher (ECR), there is only a brief window of time during which you can qualify for such opportunities. I’m incredibly grateful for this recognition, which would not have been possible without the support of my university and the mentorship of my colleagues in the Department of Mathematics.”