EDUCATIONAL BACKGROUND

• PhD in Mathematics, National Taiwan University (2009)

• MS in Industrial Engineering, National Taiwan University (2004)

• BS in Business Administration, National Taiwan University (2002)

ACADEMIC PUBLICATIONS

1. Hung, H., Yeh, C. C., and Huang, S. Y. (2025). On the asymptotic properties of product-PCA under the high-dimensional setting. Arxiv.

2. Hung, H. and Huang, S. Y. (2025). On the efficiency-loss free ordering-robustness of product-PCA. Arxiv.

3. Hung, H., Huang, S. Y., and Eguchi, S. (2023). Robust self-tuning semiparametric PCA for contaminated elliptical distribution. IEEE Transactions on Signal Processing, 70, 5885-5897. code 

4. Hung, H., Huang, S. Y., and Ing, C. K. (2022). A generalized information criterion for high-dimensional PCA rank selection. Statistical Papers, 63, 1295–1321. code

5. Huang, M. Y. and Hung, H. (2022). A Review on sliced inverse regression, sufficient dimension reduction, and applications. Statistica Sinica, 32, 2297-2314.

6. Li, C. J., Huang, P. H., Ma, Y. T., Hung, H., and Huang, S. Y. (2022). Robust aggregation for federated learning by minimum gamma-divergence estimation. Entropy, 24(5), 686.

7. Hung, H. (2019). A robust removing unwanted variation-testing procedure via gamma-divergence. Biometrics 75, 650-662. code

8. Hung, H. and Huang, S. Y. (2019). Sufficient dimension reduction via random-partitions for the large-p-small-n problem. Biometrics 75, 245-255. code

9. Hung, H. and Jou, Z. Y. (2019). A low-rank based estimation-testing procedure for matrix-covariate regression. Statistica Sinica 29, 1025-1046.

10. Hung, H., Jou, Z. Y., and Huang, S. Y. (2018). Robust mislabel logistic regression without modeling mislabel probabilities. Biometrics 74, 145-154. code

11. Hung, H. and Lu, H. H. (2017). A review on the generalization of sufficient dimension reduction methods with the additional information. WIREs Computational Statistics, e1401. (doi: 10.1002/wics.1401)

12. Hung, H., Liu, C. Y., and Lu, H. S. (2016). Sufficient dimension reduction with additional information. Biostatistics 17, 405-421.

13. Hung, H., Lin, Y. T., Wang, C. C., Chen, P., Huang, S. Y., and Tzeng, J. Y. (2016). Detection of gene-gene interactions using multistage sparse and low-rank regression. Biometrics 72, 85-94.

14. Chen, T. L., Hsieh, D. N., Hung, H., Tu, I. P., Wu, P. S., Wu, Y. M., Chang, W. H., and Huang, S. Y. (2014). gamma-SUP: a clustering algorithm for cryo-electron microscopy images of asymmetric particles. The Annals of Applied Statistics 8, 259-285. code

15. Hung, H. and Wang, C. C. (2013). Matrix variate logistic regression model with application to EEG data. Biostatistics 14, 189-202. code

16. Hung, H. and Wang, C. C. (2013). Rejoinder to doi:10.1093/biostatistics/kxs039. Biostatistics 14, 406-407.

17. Chen, P., Hung, H., Komori, O., Huang, S. Y., and Eguchi, S. (2013). Robust independent component analysis via minimum gamma-divergence estimation. IEEE Journal of Selected Topics in Signal Processing 7, 614-624.

18. Liu, J. R., Kuo, P. H., Hung, H. (2013). A robust re-rank approach for feature selection and its application to pooling-based GWA study. Computational and Mathematical Methods in Medicine, Article ID: 860673.

19. Hung, H. (2012). A two-stage dimension reduction method for transformed responses and its applications. Biometrika 99, 865-877.

20. Hung, H., Wu, P. S., Tu, I. P., and Huang, S. Y. (2012). On multilinear principal component analysis of order-two tensors. Biometrika 99, 569-583. code

21. Hung, H. and Chen, A. (2012). Test of covariance changes without a large sample and its application to fault detection and classification. Journal of Process Control 22, 1113-1121.

22. Hung, H. and Chiang, C. T. (2011). Nonparametric methodology for the time-dependent partial area under the ROC curve. Journal of Statistical Planning and Inference 141, 3829-3838.

23. Hung, H. and Huang, S. Y. (2010). Discussion of "Envelope models for parsimonious and efficient multivariate linear regression''. Statistica Sinica 20, 981-987.

24. Hung, H. and Chiang, C. T. (2010). Optimal composite markers for time-dependent receiver operating characteristic curves with censored survival data. Scandinavian Journal of Statistics 37, 664-679.

25. Hung, H. and Chiang, C. T. (2010). Estimation methods for time-dependent AUC models with survival data. Canadian Journal of Statistics 38, 8-26.

26. Chiang, C. T. and Hung, H. (2010). Nonparametric estimation for time-dependent AUC, Journal of Statistical Planning and Inference 140, 1162-1174.

27. Chiang, C. T., Wang, S. H., and Hung, H. (2009). Random weighting and edgeworth expansion for the nonparametric time-dependent AUC estimator. Statistica Sinica 19, 969-979.