معرفی
Hung Tong is an Assistant Professor in the Department of Mathematics at Rowan University's College of Science & Mathematics. He specializes in applied statistics and computational methods, with a focus on model-based clustering and handling complex data challenges like missing values, skewness, and outliers. His work intersects interdisciplinary consulting projects in public health, ecology, chemistry, education, nutrition, and business.
Education:
- Ph.D., Applied Statistics, The University of Alabama
- M.S., Statistics, San Jose State University
- B.S., Applied Mathematics, San Jose State University
Research Interests: Dr. Tong develops flexible clustering techniques and statistical software for incomplete or high-dimensional datasets. He emphasizes robust methodologies capable of addressing real-world data imperfections, such as skewness and outliers, to improve accuracy in data analysis. His contributions bridge theoretical advancements with practical tools for researchers across disciplines.
Publications & Software: Key works include the MixtureMissing R package for robust clustering with missing data and studies on directional outlier detection and computational strategies for model-based clustering. His publications span journals like the Journal of Classification and Advances in Data Analysis and Classification.
Teaching & Consulting: In Spring 2025, he teaches 'CONCEPTS STAT DATA ANALYSIS' and 'PROBABILITY/RANDOM VARIABLES'. Office hours are MW 2:00–3:00pm, T 10:00–11:00am, or by appointment. He is affiliated with the Statistical Consulting Group, offering expertise to researchers and students.
