黄恒振

教授， 硕士生导师(学术型和专业型)

Email:  hzhuang@mailbox.gxnu.edu.cn

教育工作经历

专任教师  2016年至今    广西师范大学数学与统计学院

博士后   2014.09—2016.09   美国乔治城大学医学院

博士     2010.09—2014.07    南开大学数学学院

试验设计(Design of Experiment)，计算机试验(Computer Experiment)，药物组合设计(Drug Combination Design)

高等数学、线性代数、概率论与数理统计、实验设计与建模、抽样调查理论

[23] Wang, X., Gai, Y. and Huang, H. (2025+). Design Based Global Sensitivity Analysis for Quantity-Permutation Models. Technometrics,  DOI - 10.1080/00401706.2025.257441.  

[22] Huang, H. and Liu, M. Q. (2025+). Two-Dimensional Maximin Power Designs for Combination Experiments of Drugs. Communications in Mathematics and Statistics, DOI: 10.1007/s40304-023-00388-w.

[21] Fang, H. B., Huang, H., Yuan, A., Fan, R. and Tan, M. (2024). Integrative Classification Using Structural Equation Modeling of Homeostasis. Statistics in Biosciences, 16, 742-760 .

[20] Mo, G., Wang, Y., Wei, S., Li, J., Huang, H. and Zhang, X. (2024). Construction of Two-level Component Orthogonal Arrays for Order-of-Addition Experiments. Communications in Statistics-Theory and Methods, 53, 8857-8865.

[19] Wang, X. and Huang, H. (2024). Nested symmetrical Latin hypercube designs. Statistical Papers,65, 4299-4330.

[18] Huang, H. (2024).Design for Order-of-Addition Experiments with Two-level Components. Scandinavian Journal of Statistics,51, 142-170.

[17] Huang, H., Liu, M. Q., Tan, M. and Fang, H. B. (2023). Design and Modeling for Drug Combination Experiments with Order Effects. Statistics in Medicine, 42, 1353-1376.

[16] Wang, X. and Huang, H. (2023). Group Symmetric Latin Hypercube Designs for Symmetrical Global Sensitivity Analysis. Computational Statistics & Data Analysis, 179, 107625.

[15] Zhang, B., Huang, H. and Chen, J. (2023). Estimation of Large-Dimensional Covariance Matrices via Second-Order Stein-Type Regularization. Entropy, 25, 53.

[14] Yin, C. and Huang, H. (2021). A Method of Constructing Optimal Sliced Uniform Designs under Discrete Discrepancy. Stat, 10, e388.

[13] Huang, H., Yu, H., Liu, M. Q. and Wu, D. (2021). Construction of Uniform Designs and Complex-structured Uniform Designs via Partitionable t-designs. Statistica Sinica, 31, 1689-1706.

[12] Huang, H. (2021). Construction of Component Orthogonal Arrays with any Number of Components. Journal of Statistical Planning and Inference,213, 72-79.

[11] Huang, H. and Chen, X. (2021). Compromise Design for Combination Experiment of Two Drugs.Computational Statistics & Data Analysis, 157, 107150.

[10] Huang, H. (2021). Multi-drug Combination Designs with Experiments in silico. Statistics and Its Interface, 14, 373-388.

[9] Li, W., Guo, B., Huang, H. and Liu, M. Q. (2021). Semifoldover Plans for Three-level Orthogonal Arrays with Quantitative Factors. Statistical Papers, 62, 2691-2709.

[8] Huang, H., Lin, D. K. J., Liu, M. Q. and Zhang, Q. (2020). Variable Selection for Kriging in Computer Experiments. Journal of Quality Technology, 52, 40-53.

[7] Huang, H., Fang, H. B., and Tan, M. (2018). Experimental Design for Multi-drug Combination Studies Using Signaling Networks. Biometrics, 74, 538-547.

[6] Huang, H., Zhou, S., and Liu, M. Q. (2017).Acceleration of The Stochastic Search Variable Selection via Componentwise Gibbs Sampler.Metrika,80, 289-308.

[5] Tan, M., Fang, H. B., Huang, H., and Yang, Y. (2016) Design and Statistical Analysis of Multi-drug Combinations in Preclinical Studies and Clinical Trials. In book Statistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics. Page 215-234. Lin, J., Wang, B., Hu, X., Chen, K., Liu, R. (Eds.) Springer, New York & Switzerland.

[4] Huang, H., Lin, D. K. J., Liu, M. Q. and Yang, J. (2016).Computer Experiments with Both Qualitative and Quantitative Variables. Technometrics,58, 495-507.

[3] Chen, H., Huang, H., Lin, D. K. J. and Liu, M. Q. (2016).Uniform Sliced Latin Hypercube Designs.Applied Stochastic Models in Business and Industry,32, 574-584.

[2] Huang, H., Yang, J.and Liu, M. Q. (2014).Functionally Induced Priors for Componentwise Gibbs Sampler in The Analysis of Supersaturated Designs.Computational Statistics & Data Analysis, 72,1-12.

[1] Huang, H., Yang, J. and Liu, M. Q. (2014). Construction of Sliced (Nearly) Orthogonal Latin Hypercube Designs. Journal of Complexity, 30, 355-365.