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. MixtureMissing: An R package for robust and flexible model-based clustering with incomplete data. Journal of Statistical Software. (Forthcoming)
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.
Spring 2026 - Class Schedule
20896 - DS - 01101-1 IN-DEPTH INTRODUCTION TO DATA MWF 11:00am - 12:15pm Robinson 324
20802 - MATH - 03612-1 MASTERS THESIS Glassboro
20894 - STAT - 02515-1 APPLIED MULTIVARIATE DATA ANLY M 2:00pm - 3:15pm James 3117
M 3:30pm - 4:45pm James 3117
Spring 2026 - Office Hours
By appointment via tong@rowan.edu