Rate My Professor Don Hong

Hong's research focuses on approximation theory, splines, wavelets, and their applications to high-dimensional data analysis, including quantitative medical data processing, proteomics, hyperspectral imaging, biostatistics, and actuarial science. He has co-authored two prominent books: Real Analysis with an Introduction to Wavelets and Applications (Elsevier/Academic Press, 2005, with Jianzhong Wang and Robert Gardner) and Quantitative Medical Data Analysis Using Mathematical Tools and Statistical Techniques (World Scientific, 2007, with Yu Shyr). Key publications include "Spaces of Bivariate Spline Functions over Triangulations" (Approximation Theory and Applications, 1991), "Stability of Optimal Order Approximation by Bivariate Splines over Arbitrary Triangulations" (Transactions of the American Mathematical Society, 1995, with C.K. Chui and R.Q. Jia), "BERT Based NLP Techniques for Classification and Severity Modeling in Basic Warranty Data Study" (Insurance: Mathematics and Economics, 2022, with Shuzhe Xu and Chuanlong Zhang), and works on proteomic data mining and hyperspectral imaging. Hong has secured significant external funding, including NSF grants totaling over $245,000 for projects on wavelets in cancer research and classroom reform, NSA grants for workshops on medical data analysis, Casualty Actuarial Society awards such as $15,000 in 2021-2022 and the 2020 University Award, and Health and Human Services funding exceeding $740,000 for Tennessee health rate reviews. His influence extends through organizing international conferences like the Canada-China-USA Conference on Modern Techniques in Computational Mathematics (2011) and delivering invited lectures at prestigious institutions worldwide, including Peking University, City University of Hong Kong, and North China University of Technology. Under his leadership, MTSU was recognized as a Center of Actuarial Excellence.