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. (2026). MixtureMissing: An R package for robust and flexible model-based clustering with incomplete data. Journal of Statistical Software, 115(3), 1–32.

Tong, H., Zhu, X, and Melnykov, Y. (2025). Double-layer conditional mixture model for model-based clustering and automatic component merging. Journal of Classification.

Tong, H. and Tortora, C. (2024). Missing values and directional outlier detection in model-based clustering. Journal of Classification, 41, 480–53.

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.