Biography
Dr. Hsin-Hsiung “Bill” Huang is a Professor of Statistics and Data Science at the University of Central Florida (UCF) and a U.S. citizen of Taiwanese American heritage. He earned his Ph.D. in Statistics from the University of Illinois at Chicago, an M.S. in Statistics from the Georgia Institute of Technology, an M.S. in Mathematics from National Taiwan University, and dual B.A./B.S. degrees in Economics and Mathematics, also from National Taiwan University.
Dr. Huang’s research interests include Bayesian ultrahigh-dimensional variable selection, matrix- and tensor-variate regression, clustering, classification, dimension reduction, and statistical learning, with an emphasis on developing new statistical methodology for complex, high-dimensional, and large-scale data. His recent research spans spatiotemporal modeling, neuroimaging and medical-image reconstruction, threat and anomaly detection, genomic and phenome-wide fine mapping, and infectious-disease epidemic intelligence.
His research has been supported by multiple grants from the National Science Foundation’s Algorithms for Threat Detection (ATD) program, for which he has served as Principal Investigator, including NSF DMS-1924792 and DMS-2318925. He has also served as Principal Investigator on a Lockheed Martin research project involving anomaly detection in high-dimensional missile simulation data. His biomedical research is supported by the National Institutes of Health (NIH), where he serves as Principal Investigator of a National Institute of Allergy and Infectious Diseases (NIAID) R01 award (1R01AI206603-01) focused on Bayesian phenotyping, multilayer network inference, and epidemic intelligence for sexually transmitted infections. He also serves as a Co-Investigator on a National Institute of Neurological Disorders and Stroke (NINDS) R01 award (1R01NS133094-01A1).
In addition to his research and teaching, Dr. Huang contributes to the broader statistical community through editorial and professional service. He serves as an Associate Editor of Statistics and Computing, a leading international journal in computational statistics and statistical computing, and as an Associate Editor of Frontiers in Applied Mathematics and Statistics. He is also an elected member of the International Statistical Institute (ISI).
Dr. Huang’s research team at UCF achieved first-place finishes in the NSF ATD Challenge competitions for three consecutive years, from 2021 through 2023. His honors include the UCF Research Incentive Award (RIA) in 2021 and again in 2026, a UCF College of Sciences Seed Grant in 2023–24, the UCF Outstanding Instruction Award in 2024, the UCF Office of Research Mentoring Program Award in 2025, Outstanding Post-Tenure Review recognition in 2025, and the 2025 UCF College of Sciences OSCaR Award for Outstanding Scholarship, Creative Works, and Research.
Dr. Huang was selected to the Fulbright Specialist Roster in Statistics and Data Science for 2025–2028. Through the Fulbright Specialist Program, he completed an international academic exchange at Al Khwarizmi University in Uzbekistan in April and May 2026, contributing to research collaboration and training in statistics and data science.
Research
Bayesian modeling and computation, robust dimension reduction, manifold learning, ultrahigh-dimensional variable selection, Bayesian cluster Process, algorithms for threat detection, medical image reconstruction, missingness imputation.
Publications
1. Huang HH*, F Yu F and T Zhang* (2024) Robust Sufficient Dimension Reduction via -Distance Covariance. Journal of Nonparametric Statistics, 1(16) 1048-5252. DOI: 10.1080/10485252.2024.2313137
2. Zhang W, Ma Z, Ho HH*, Yang S, Habiger JD, Huang HH, Huang Y (2024) Multi-omics Integrative Analysis for Incomplete Data Using Weighted p- value Adjustment Approaches. Journal of Agricultural, Biological, and Environmental Statistics. https://doi.org/10.1007/s13253-024-00603-3
3. Chen Z, An L, Kao CM, Huang HH (2023) The properties of the positronium lifetime image reconstruction based on maximum likelihood estimation. Bio- Algorithms and Med-Systems 19 (1)
4. Huang HH, Yu F, Fan X, and Zhang T (2023) A Framework of Regularized Low-Rank Matrix Models for Regression and Classification. Statistics and Computing 34 (10), https://doi.org/10.1007/s11222-023-10318
5. He Q and Huang HH (2023) A Framework of Zero-Inflated Bayesian Negative Binomial Regression Models for Spatiotemporal Data. Journal of Statistical Planning and Inference. Volume 229, 106098, ISSN 0378-3758,
6. Huang HH and He Q (2023) Statistical modeling of Peromyscus maniculatus (deer mouse) amounts per trap with spatiotemporal data. Japanese Journal of Statistics and Data Science. https://doi.org/10.1007/s42081-023-00212-3
7. Chen CW and Huang HH (2023) Unsupervised Vessel Trajectory Reconstruction. Front. Appl. Math. Stat. 9, doi: 10.3389/fams.2023.1124091
8. He Q, Harrison CW, and Huang HH (2023) Detection of Anomalies in Traffic Flows with Large Amounts of Missing Data. The New England Journal of Statistics in Data Science, 1-11
9. Yu Z, Yang J, and Huang HH (2023) Smoothing Regression and Impact Measures for Accidents of Traffic Flows. Journal of Applied Statistics DOI: 10.1080/02664763.2023.2175799
10. Huang HH and He Q (2022) Nonlinear regression analysis. International Encyclopedia of Education 4th Edition
11. Harrison CW, He Q, and Huang HH (2022) Clustering Gene Expressions Using the Table Invitation Prior Genes 13 (11), 2036
12. Fan CW, Drumheller K, Chen IH, and Huang HH (2022) College students’ sleep difficulty during COVID-19 and correlated stressors: A large-scale cross-sessional survey study. Sleep Epidemiology 1, 100004
13. Huang HH and Yang J (2020) Affine-Transformation Invariant Clustering Models. Journal of Statistical Distributions and Applications 7 (1), 1-24
14. Huang HH and Zhang T (2020) Robust discriminant analysis using multi-directional projection pursuit. Pattern Recognition Letters, 138, 651-656.
15. Huang HH, Condor A, and Huang HJ. (2020) Classification of EEG Motion Artifact Signals Using Spatial ICA. Statistical Modeling in Biomedical Research: Contemporary Topics and Voices in the Field.
16. Zhu H, Huang HH, and Pang S. (2019) Photon allocation strategy in region-of-interest tomographic imaging. IEEE Transactions on Computational Imaging. DOI: 10.1109/TCI.2019.2922477
17. Huang HH, Wang Z, and Chung W. (2019) Efficient Parameter Selection for Support Vector Machines. Enterprise Information Systems. doi.org/10.1080/17517575.2019.1592233
18. Huang HH and Girimurugan SB. (2019) Discrete Wavelet packet transform based discriminant analysis for genome sequences data. Statistical Applications in Genetics and Molecular Biology. 20180045
19. Huang HH, Hao S, Alacorn S, and Yang J. (2018) Comparisons of classification methods for viral genomes and protein families using alignment-free vectorization. Statistical Applications in Genetics and Molecular Biology, 17(4), 20180004.
20. Huang HH and Girimurugan SB. (2018) A novel real-time genome comparison method using discrete wavelet transform. Journal of Computational Biology, 25(4), 406- 416
21. Huang HH, Wang Z, and Chung W. (2017) Efficient parameter selection for SVM: The case of business intelligence categorization, 2017 IEEE International Conference on Intelligence and Security Informatics (ISI) proceeding, 158-160.
22. Huang HH and Yu C. (2016) Clustering DNA sequences using the out-place measure with reduced n-gram. Journal of Theoretical Biology, 406, 61-72.
23. Huang HH. (2016) Ensemble method of k-mer and natural vector for the phylogenetic analysis of multiple-segmented viruses. Journal of Theoretical Biology, 398, 136-144.
24. Lu AT, Austin E, Bonner A, Huang HH, Cantor RM. (2014) Applications of machine learning and data mining methods to detect associations of rare and common variants with complex traits. Genet Epidemiol, 38 Suppl 1:S81-85.
25. Huang HH, Yu C, Hernandez T, Zheng H, Yau SC, He RL, Yang J, and Yau SST. (2014) Global Comparison of multiple-segmented Viruses in 12-dimensional Genome Space. Molecular Phylogenetics and Evolution, 81, 29-36.
26. Huang HH, Xu T and Yang J. (2014) Comparing logistic regression, support vector machines, and permanental classification methods in predicting hypertension. BMC Proceedings, 8(Suppl 1):S96
27. Yu C, Hernandez T, Zheng H, Yau SC, Huang HH, He RL, Yang J, and Yau SST. (2013) Real time classification of Viruses in 12 Dimensions. PLoS One, 8(5): e17293.
28. Huang HH and Yeh YR. (2011) Iterative algorithm for robust kernel principal component analysis. Neurocomputing, 74(18), 3921-3930
29. Huang HH, Hsiao CK and Huang SY. (2010) Statistics: Nonlinear regression. International Encyclopedia of Education, 3rd Edition, London, Elsevier. 339-346
Technical Reports
1. Huang HH, Hsiao CK, Huang SY. (2008) Nonlinear regression analysis. Academia Sinica Technical Report, 2008-8
2. Chen H and Huang HH. (2008) Model selection consistency of Cp-LASSO in linear regression with orthonormal regressors. Academia Sinica Technical Report, 2008-9
Submitted
1. Zhu Z, Sofa H, Kao CM and Huang HH (2023) A statistical reconstruction algorithm for positronium lifetime imaging using time-of-flight positron emission tomography.
2. Wang SH, Bai R, and Huang HH (2023) Mixed-type Multivariate Bayesian Sparse Variable Selection with Shrinkage Priors.
3. T Lu, C Chen, Huang HH, P Kochunov, E Hong, S Chen (2024) Multiple Imputation Method for High-Dimensional Neuroimaging Data.
Courses
- STA6714 Data Preparation – Spring 2024
- STA7348 Bayesian Modeling and Computation – Spring 2024, 2023, 2021, 2020
- STA4241 Statistical Learning – Fall 2023, 2022
- STA7734 Statistical Asymptotic Theory in Big Data – Fall 2023, 2022, 2020
- STA5505 Categorical Data Methods – Summer 2023, 2020
- STA6223 Conventional Survey Methods – Spring 2023
- STA4241 Statistical Learning – Fall 2023, 2022
- STA 5104 – Advanced Computer Processing of Statistical Data – Summer 2022, 2021
- STA6704 Data Mining Methodology II – Spring 2020