Hung Tong, Ph.D.
Hung Tong, Ph.D.
Hung Tong, Ph.D.
Assistant Professor
Biography
Websites:
Google Scholar
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 Expertise:
Cluster analysis | Classification | Mixture Modeling | Computational Statistics
I am a statistician with research interests in cluster analysis, classification, and computational statistics. One major focus of my work concerns the development of flexible model-based clustering methods and statistical software for complex data, including missing data, data with skewness and outliers, and high-dimensional data. I also enjoy consulting for researchers across various fields; my past experience includes projects in public health, ecology, chemistry, education, nutrition, and business.
Professional Memberships:
American Statistical Association (www.amstat.org)
Society of Classification
Selected Publications:
Tong, H. and Tortora, C. (2023). Missing values and directional outlier detection in model-based clustering. Journal of Classification.
Tong, H. and Tortora, C. (2022). Model-based clustering and outlier detection with missing data. Advances in Data Analysis and Classification, 16(1):5–30.
Fall 2024 - Office Hours
MW 2:00pm-3:00pm, T 10:00am-11:00am, by appointment at tong@rowan.edu