Publications of Hongquan Xu (google scholar page)

• Selected recent publications on experimental design (fractional factorial designs and composite designs)

• Xu, H., Jaynes, J., and Ding, X. (2014). Combining Two-Level and Three-Level Orthogonal Arrays for Factor Screening and Response Surface Exploration. Statistica Sinica, 24, 269-289.
• Tang, Y. and Xu, H. (2014). Permuting Regular Fractional Factorial Designs for Screening Quantitative Factors. Biometrika, 101, 333-350.
• Zhou, Y. D. and Xu H. (2014). Space-filling fractional factorial designs. Journal of the American Statistical Association, 109, 1134-1144.
• Gromping, U. and Xu, H. (2014). Generalized resolution for orthogonal arrays. Annals of Statistics, 42, 918-939.
• Xu, H. (2015). Nonregular factorial and supersaturated designs. In Handbook of Design and Analysis of Experiments, eds A. Dean, M. Morris, J. Stufken and D. Bingham, Chapman and Hall/CRC, Series: Chapman & Hall/CRC Handbooks of Modern Statistical Methods, 339-370.
• Zhou, Y. D. and Xu, H. (2017). Composite designs based on orthogonal arrays and definitive screening designs. Journal of the American Statistical Association, 112:520, 1675-1683.
• Vazquez, A. R. and Xu, H. (2019). Construction of Two-Level Nonregular Designs of Strength Three With Large Run Sizes. Technometrics, 61, 341-353.
• Tang, Y. and Xu, H. (2021). Wordlength Enumerator for Fractional Factorial Designs. Annals of Statistics, 49, 255-271. [pdf]

• Selected recent publications on computer experiments (maximin distance designs and space-filling designs)
• Zhou, Y. and Xu, H. (2015). Space-filling properties of good lattice point sets. Biometrika, 102 (4), 959-966.
• Xiao, Q. and Xu, H. (2017). Construction of Maximin Distance Latin Squares and Related Latin Hypercube Designs. Biometrika, 104, 455-464.
• Xiao, Q. and Xu, H. (2018). Construction of Maximin Distance Designs via Level Permutation and Expansion. Statistica Sinica, 28, 1395-1414.
• Wang, Y., Yang, J. and Xu, H. (2018). On Connection Between Maximin Distance Designs and Orthogonal Designs. Biometrika, 105, 471-477.
• Wang, L., Xiao, Q. and Xu, H. (2018). Optimal Maximin L1-distance Latin Hypercube Designs Based on Good Lattice Point Designs. Annals of Statistics, 46(6B), 3741-3766. [pdf]
• Sun, F., Wang, Y. and Xu, H. (2019). Uniform Projection Designs. Annals of Statistics, 47, 641-661. [pdf]
• Wang, Y., Sun, F. and Xu, H. (2022). On design orthogonality, maximin distance and projection uniformity for computer experiments. Journal of the American Statistical Association, 117, 375-385.
• Tian, Y. and Xu, H. (2022). A Minimum Aberration Type Criterion for Selecting Space-Filling Designs. Biometrika 109(2), 489-501.
• Yin, Y., Wang, L. and Xu, H. (2023). Construction of Maximin L_1-Distance Latin Hypercube Designs. Electronic Journal of Statistics, 17, 3942-3968.
• Vazquez, A. R. and Xu, H. (2024). An integer programming algorithm for constructing maximin distance designs from good lattice point sets. Statistica Sinica, 34(3), 1347-1366.
• Tian, Y. and Xu, H. (2024). Stratification Pattern Enumerator and its Applications. Journal of the Royal Statistical Society Series B: Statistical Methodology, 86(2), 364-385.
• Shi, C. and Xu, H. (2024). A Projection Space-Filling Criterion and Related Optimality Results. Journal of the American Statistical Association, 119(548), 2658-2669.
• Yuan, R., Yin, Y., Xu, H., and Liu, M.-Q. (2025). A Construction Method for maximin L1-distance Latin hypercube designs. Statistica Sinica, 35(1), 249-272.
• Tian, Y. and Xu, H. (2025+). A Stratified L2-Discrepancy and its Applications. Journal of the Royal Statistical Society Series B: Statistical Methodology, published: 10 September 2025.

• Selected publications on order-of-addition experiments
• Wang, A., Xu, H. and Ding, X. (2020). Simultaneous Optimization of Drug Combination Dose-Ratio-Sequence with Innovative Design and Active Learning. Advanced Therapeutics, 3(4), 1900135. https://doi.org/10.1002/adtp.201900135
• Yang, J., Sun, F. and Xu, H. (2021). A Component-Position Model, Analysis and Design for Order-of-Addition Experiments. Technometrics, 63, 212-224..
• Xiao, Q. and Xu, H. (2021). A Mapping-based Universal Kriging Model for Order-of-addition Problems in Drug Combination Studies. Computational Statistics and Data Analysis, 157, 107155.
• Stokes, Z. and Xu, H. (2022). A Position-Based Approach for Design and Analysis of Order-of-Addition Experiments. Statistica Sinica, 32(3), 1467-1488.
• Stokes, Z. and Xu, H. (2024). Designs for Order-of-Addition Screening Experiments. Statistica Sinica, 34(1), 34(1), 399--419
• Stokes, Z., Wong, W. K., and Xu, H. (2024). Metaheuristic Solutions to Order-of-Addition Design Problems. Journal of Computational and Graphical Statistics, 33(3), 1006-1016.

• Selected publications on drug combination
• Jaynes, J., Ding, X., Xu, H., Wong, W. K., and Ho, C.-M. (2013). Application of Fractional Factorial Designs to Study Drug Combinations. Statistics in Medicine, 32, 307--318.
• Ding, X., Xu, H., Hopper, C., Yang, J. and Ho, C.-M. (2013). Use of fractional factorial designs in antiviral drug studies. Quality and Reliability Engineering International, 29, 299--304.
• Ning, S., Xu, H., Al-Shyoukh, I., Feng, J., and Sun, R. (2014). An Application of a Hill-based Response Surface Model for a Drug Combination Experiment on Lung Cancer. Statistics in Medicine, 33, 4227-4236.
• Ding, X., Liu, W., Weiss, A., Li, Y., Wong, I., Griffioen, A., van den Bergh, H., Xu, H., Nowak-Sliwinska, P. and Ho, C.-M. (2014). Discovery of a low order drug-cell response surface for applications in personalized medicine. Physical Biology, 11, 065003.
• Jaynes, J., Zhao, Y., Xu, H., and Ho, C.-M. (2016). Use of Orthogonal Array Composite Designs to Study Lipid Accumulation in a Cell-Free System. Quality andReliability Engineering International, 32, 1965-1974.
• Xiao, Q., Wang, L. and Xu, H. (2019). Application of Kriging Models for a Drug Combination Experiment on Lung Cancer. Statistics in Medicine, 38, 236-246.
• Ding, X., Chang, V. H. S., Li, Y., Xu, H., Ho, C.-M., Ho, D. and Yen, Y. (2020). Harnessing an Artificial Intelligence Platform to Dynamically Individualize Combination Therapy for Treating Colorectal Carcinoma in a Rat Model. Advanced Therapeutics, 3(4), 1900127. https://doi.org/10.1002/adtp.201900127
• Wang, A., Xu, H. and Ding, X. (2020). Simultaneous Optimization of Drug Combination Dose-Ratio-Sequence with Innovative Design and Active Learning. Advanced Therapeutics, 3(4), 1900135. https://doi.org/10.1002/adtp.201900135
• Luna, J., Jaynes, J., Xu, H., Wong, W. K. (2022). Orthogonal Array Composite Designs for Drug Combination Experiments with Applications to Tuberculosis. Statistics in Medicine, http://doi.org/10.1002/sim.9423

• Publications on Functional Data Analysis
• Shen, Q. and Xu, H. (2007). Diagnostics for Linear Models With Functional Responses. Technometrics, 49, 26-33.
• Yang, X., Shen, Q., Xu, H. and Shoptaw, S. (2007). Functional Regression Analysis using an F Test for Longitudinal Data with Large Numbers of Repeated Measures. Statistics in Medicine, 26, 1552-1566.
• Xu, H., Shen, Q., Yang, X. and Shoptaw, S. (2011). A Quasi F Test for Functional Linear Models With Functional Covariates and its Application to Longitudinal Data. Statistics in Medicine, 30, 2842-2853.
• Other selected publications

• Xu, H., Wu, P., Wu, C. F. J., Tidwell, C. and Wang, Y. (2002). A smooth response surface algorithm for constructing gene regulatory network. Physiological Genomics, 11, 11-20. US patent no. 60/297299.
• Deng, L. Y. and Xu, H. (2003). A System of High-dimensional, Efficient, Long-cycle and Portable Uniform Random Number Generators. ACM Transactions on Modeling and Computer Simulation, 13, 299-309. [Online supplement]
• Wang, L., Elmstedt, J., Wong, W. K., and Xu, H. (2021). Orthogonal Subsampling for Big Data Linear Regression. Annals of Applied Statistics, 15(3), 1273-1290.
• Burton, H., Xu, H. and Yi, Z. (2021). Design of Computer Experiments for Developing Seismic Surrogate Models. Earthquake Spectra, in press. [pdf]

All publications

• Refereed journal publications

1. Wang, G., Zhu, K., Ye, J., Xu, H. and Liang, P. (1996). Seafloor nodules image recognition system. Geological Review 42, 560--563 (in Chinese).
2. Xu, H. and Shen, S. (1998). Uniform designs based on computer experiments. Applied Mathematics: A Journal of Chinese Universities Series A 13, 167--174 (in Chinese).
3. Shen, S. and Xu, H. (1998). Information criterion in experimental design. Bulletin of the Hong Kong Mathematical Society 2, 65--73.
4. Xu, H. (1999). Universally optimal designs for computer experiments. Statistica Sinica, 9, 1083-1088.
5. Xu, H. and Wu, C. F. J. (2001). Generalized minimum aberration for asymmetrical fractional factorial designs. Annals of Statistics, 29, 1066-1077.
6. Xu, H., Wu, P., Wu, C. F. J., Tidwell, C. and Wang, Y. (2002). A smooth response surface algorithm for constructing gene regulatory network. Physiological Genomics, 11, 11-20. US patent no. 60/297299.
7. Xu, H. (2002). An algorithm for constructing orthogonal and nearly-orthogonal arrays with mixed levels and small runs. Technometrics, 44, 356-368. (C source code ) (S source code )
8. Xu, H. (2003). Minimum moment aberration for nonregular designs and supersaturated designs. Statistica Sinica, 13, 691-708.
9. Deng, L. Y. and Xu, H. (2003). A System of High-dimensional, Efficient, Long-cycle and Portable Uniform Random Number Generators. ACM Transactions on Modeling and Computer Simulation, 13, 299-309. [Online supplement]
10. Xu, H., Cheng, S.W. and Wu, C. F. J. (2004). Optimal Projective Three-Level Designs for Factor Screening and Interaction Detection. Technometrics, 46, 280-292.
11. Xu, H. and Deng, L. Y. (2005). Moment Aberration Projection for Nonregular Fractional Factorial Designs. Technometrics, 47, 121-131.
12. Xu, H. (2005a). Some Nonregular Designs From the Nordstrom and Robinson Code and Their Statistical Properties. Biometrika, 92, 385-397. [pdf file]
13. Xu, H. (2005b). A catalogue of three-level regular fractional factorial designs. Metrika, 62, 259-281. [online supplement].
14. Xu, H. and Wu, C. F. J. (2005). Construction of Optimal Multi-Level Supersaturated Designs. Annals of Statistics, 33, 2811-2836. [Online supplement and Xu and Wu (2003) UCLA Statistics Electronic Publications preprint 356]
15. Xu, H. and Lau, S. (2006). Minimum Aberration Blocking Schemes for Two- and Three-Level Fractional Factorial Designs. Journal of Statistical Planning and Inference, 136, 4088-4118.
16. Xu, H. (2006). Blocked Regular Fractional Factorial Designs With Minimum Aberration. Annals of Statistics, 34, 2534-2553.
17. Shen, Q. and Xu, H. (2007). Diagnostics for Linear Models With Functional Responses. Technometrics, 49, 26-33.
18. Yang, X., Shen, Q., Xu, H. and Shoptaw, S. (2007). Functional Regression Analysis using an F Test for Longitudinal Data with Large Numbers of Repeated Measures. Statistics in Medicine, 26, 1552-1566.
19. Xu, H. and Wong, A. (2007). Two-Level Nonregular Designs From Quaternary Linear Codes. Statistica Sinica, 17, 1191-1213.
20. Xu, H. and Cheng, C. -S. (2008). A Complementary Design Theory for Doubling. Annals of Statistics, 36, 445-457.
21. Xu, H. (2009). Algorithmic Construction of Efficient Fractional Factorial Designs With Large Run Sizes. Technometrics, 51, 262-277.
22. Phoa, F. K. H. and Xu, H. (2009). Quarter-Fraction Factorial Designs Constructed via Quaternary Codes. Annals of Statistics, 37, No. 5A, 2561-2581.
23. Phoa, F. K. H., Pan, Y.-H. and Xu, H. (2009). Analysis of Supersaturated Designs via the Dantzig Selector. Journal of Statistical Planning and Inference, 139, 2362-2372. [Preprint]
24. Xu, H., Phoa, F. K. H. and Wong, W. K. (2009). Recent Developments in Nonregular Fractional Factorial Designs. Statistics Surveys, 3, 18-46. DOI: 10.1214/08-SS040.
25. Phoa, F. K. H., Xu, H. and Wong, W. K. (2009). The use of nonregular fractional factorial designs in combination toxicity studies. Food and Chemical Toxicology, 47, 2183-2188. [Preprint]
26. Phoa, F. K. H., Wong, W. K. and Xu, H. (2009). The Need of Considering the Interactions in the Analysis of Screening Designs. Journal of Chemometrics, 23, 545-553. [Preprint]
27. Xu, H., and Mee, R. W. (2010). Minimum Aberration Blocking Schemes for 128-Run Designs. Journal of Statistical Planning and Inference, 140, 3213-3229. [Preprint]
28. Zhang, R., Phoa, F. K. H., Mukerjee, R. and Xu, H. (2011). A Trigonometric Approach to Quaternary Code Designs with Application to One-Eighth and One-Sixteenth Fractions. Annals of Statistics, 39, No. 2, 931-955.
29. Xu, H., Shen, Q., Yang, X. and Shoptaw, S. (2011). A Quasi F Test for Functional Linear Models With Functional Covariates and its Application to Longitudinal Data. Statistics in Medicine, 26, 1552-1566.
30. Phoa, F. K. H., Mukerjee, R. and Xu, H. (2012). One-Eighth- and One-Sixteenth-Fraction Quaternary Code Designs With High Resolution. Journal of Statistical Planning and Inference, 142, 1073-1080.
31. Chen, H.-W., Wong, W. K. and Xu, H. (2012). An Augmented Approach to the Desirability Function. Journal of Applied Statistics, 39, 599-613. DOI:10.1080/02664763.2011.605437
32. Tang Y., Xu H. and Lin D. K. J. (2012). Uniform fractional factorial designs. Annals of Statistics, 40, 891-907.
33. Jaynes, J., Ding, X., Xu, H., Wong, W. K., and Ho, C.-M. (2013). Application of Fractional Factorial Designs to Study Drug Combinations. Statistics in Medicine, 32, 307--318. doi:10.1002/sim.5526
34. Ding, X., Xu, H., Hopper, C., Yang, J. and Ho, C.-M. (2013). Use of fractional factorial designs in antiviral drug studies. Quality and Reliability Engineering International, 29, 299--304. DOI:10.1002/qre.1308
35. Chen, H.-W., Xu, H., and Wong, W. K. (2013). Balancing Location and Dispersion Effects for Multiple Responses. Quality and Reliability Engineering International, 29, 607-615. DOI:10.1002/qre.1411
36. Tang, Y. and Xu H. (2013). An effective construction method for multi-level uniform designs. Journal of Statistical Planning and Inference, 143, 1583-1589. DOI: 10.1016/j.jspi.2013.04.009
37. Xu, H., Jaynes, J., and Ding, X. (2014). Combining Two-Level and Three-Level Orthogonal Arrays for Factor Screening and Response Surface Exploration. Statistica Sinica, 24, 269-289. doi:10.5705/ss.2012.210
38. Tang, Y. and Xu, H. (2014). Permuting Regular Fractional Factorial Designs for Screening Quantitative Factors. Biometrika, 101, 333-350.
39. Zhou, Y. D. and Xu H. (2014). Space-filling fractional factorial designs. Journal of the American Statistical Association, 109, 1134-1144.
40. Gromping, U. and Xu, H. (2014). Generalized resolution for orthogonal arrays. Annals of Statistics, 42, 918-939.
41. Ning, S., Xu, H., Al-Shyoukh, I., Feng, J., and Sun, R. (2014). An Application of a Hill-based Response Surface Model for a Drug Combination Experiment on Lung Cancer. Statistics in Medicine, 33, 4227-4236.
42. Ding, X., Liu, W., Weiss, A., Li, Y., Wong, I., Griffioen, A., van den Bergh, H., Xu, H., Nowak-Sliwinska, P. and Ho, C.-M. (2014). Discovery of a low order drug-cell response surface for applications in personalized medicine. Physical Biology, 11, 065003. doi:10.1088/1478-3975/11/6/065003.
43. Zhou, Y. and Xu, H. (2015). Space-filling properties of good lattice point sets. Biometrika, 102 (4), 959-966. doi:10.1093/biomet/asv044.
44. Chen, H.-W., Wong, W. K. and Xu, H. (2016). Data-driven desirability function to measure patients? disease progression in a longitudinal study. Journal of Applied Statistics, 43, 783-795. doi:10.1080/02664763.2015.1077378.
45. Jaynes, J., Wong, W. K. and Xu, H. (2016). Using Blocked Fractional Factorial Designs to Construct Discrete Choice Experiments for HealthCare Studies. Statistics in Medicine, 35, 2543-2560. doi: 10.1002/sim.6882.
46. Jaynes, J., Zhao, Y., Xu, H., and Ho, C.-M. (2016). Use of Orthogonal Array Composite Designs to Study Lipid Accumulation in a Cell-Free System. Quality and Reliability Engineering International, 32, 1965-1974. doi: 10.1002/qre.1900.
47. Jaynes, J., Xu, H. and Wong, W. K. (2017). Minimum Aberration Designs for Discrete Choice Experiments. Journal of Statistical Theory and Practice, 11, 339-360. doi: 10.1080/15598608.2017.1299055.
48. Zhou, Y. D. and Xu, H. (2017). Composite designs based on orthogonal arrays and definitive screening designs. Journal of the American Statistical Association, 112:520, 1675-1683. DOI: 10.1080/01621459.2016.1228535
49. Xiao, Q. and Xu, H. (2017). Construction of Maximin Distance Latin Squares and Related Latin Hypercube Designs. Biometrika, 104, 455-464. https://doi.org/10.1093/biomet/asx006
50. Xiao, Q. and Xu, H. (2018). Construction of Maximin Distance Designs via Level Permutation and Expansion. Statistica Sinica, 28, 1395-1414. https://doi.org/10.5705/ss.202016.0423
51. Wang, Y., Yang, J. and Xu, H. (2018). On Connection Between Maximin Distance Designs and Orthogonal Designs. Biometrika, 105, 471-477. https://doi.org/10.1093/biomet/asy005
52. Wang, L., Xiao, Q. and Xu, H. (2018). Optimal Maximin L1-distance Latin Hypercube Designs Based on Good Lattice Point Designs. Annals of Statistics, 46(6B), 3741-3766. [pdf]
53. Xiao, Q., Wang, L. and Xu, H. (2019). Application of Kriging Models for a Drug Combination Experiment on Lung Cancer. Statistics in Medicine, 38, 236-246.
54. Sun, F., Wang, Y. and Xu, H. (2019). Uniform Projection Designs. Annals of Statistics, 47, 641-661. [pdf]
55. Vazquez, A. R. and Xu, H. (2019). Construction of Two-Level Nonregular Designs of Strength Three With Large Run Sizes. Technometrics, 61, 341-353.
56. Wang, A., Xu, H. and Ding, X. (2020). Simultaneous Optimization of Drug Combination Dose-Ratio-Sequence with Innovative Design and Active Learning. Advanced Therapeutics, 3(4), 1900135. https://doi.org/10.1002/adtp.201900135
57. Ding, X., Chang, V. H. S., Li, Y., Xu, H., Ho, C.-M., Ho, D. and Yen, Y. (2020). Harnessing an Artificial Intelligence Platform to Dynamically Individualize Combination Therapy for Treating Colorectal Carcinoma in a Rat Model. Advanced Therapeutics, 3(4), 1900127. https://doi.org/10.1002/adtp.201900127
58. Tang, Y. and Xu, H. (2021). Wordlength Enumerator for Fractional Factorial Designs. Annals of Statistics, 49, 255-271. [pdf]
59. Yang, J., Sun, F. and Xu, H. (2021). A Component-Position Model, Analysis and Design for Order-of-Addition Experiments. Technometrics, 63, 212-224..
60. Xiao, Q. and Xu, H. (2021). A Mapping-based Universal Kriging Model for Order-of-addition Problems in Drug Combination Studies. Computational Statistics and Data Analysis, 157, 107155.
61. Wang, L., Elmstedt, J., Wong, W. K., and Xu, H. (2021). Orthogonal Subsampling for Big Data Linear Regression. Annals of Applied Statistics, 15(3), 1273-1290.
    
    
62. Wang, Y., Sun, F. and Xu, H. (2022). On design orthogonality, maximin distance and projection uniformity for computer experiments. Journal of the American Statistical Association, 117, 375-385.
63. Tian, Y. and Xu, H. (2022). A Minimum Aberration-Type Criterion for Selecting Space-Filling Designs. Biometrika,109(2), 489-501.
64. Zhou, Q., Li, W. and Xu, H. (2023). Utilizing Individual Clear Effects for Intelligent Factor Allocations and Design Selections. Journal of Quality Technology, 55(1), 3-17.
65. Burton, H., Xu, H. and Yi, Z. (2022). Design of Computer Experiments for Developing Seismic Surrogate Models. Earthquake Spectra, 38(1), 384-406. [pdf]
66. Wang, L. and Xu, H. (2022). A Class of Multilevel Nonregular Designs for Studying Quantitative Factors. Statistica Sinica, 32, 825-845.
67. Stokes, Z. and Xu, H. (2022). A Position-Based Approach for Design and Analysis of Order-of-Addition Experiments. Statistica Sinica, 32(3), 1467-1488.
68. Wu, H., Amirfakhri, S., Hollandsworth, H., Filemoni, F., Liu, Y., Lin, H., Li, J. Y. S., Xu, H., Chien, S., Bouvet, M., and Wang, Y. (2022). Monocytes Engineered with iSNAP Inhibit Human B-Lymphoma Progression. Bioengineering & Translational Medicine, 7(2), e10285. https://doi.org/10.1002/btm2.10285.
69. Luna, J., Jaynes, J., Xu, H., Wong, W. K. (2022). Orthogonal Array Composite Designs for Drug Combination Experiments with Applications to Tuberculosis. Statistics in Medicine, 41(17), 3380--3397.
70. Wang, L., Xu, H. and Liu, M.-Q. (2023). Fractional factorial designs for Fourier cosine models. Metrika, 86, 373--390.
71. Shi, C., Chiu, A. K., and Xu, H. (2023). Evaluating Designs for Hyperparameter Tuning in Deep Neural Networks. The New England Journal of Statistics in Data Science, 1(3), 334-341.
72. Yin, Y., Wang, L. and Xu, H. (2023). Construction of Maximin L1-Distance Latin Hypercube Designs. Electronic Journal of Statistics, 17, 3942-3968.
73. Stokes, Z. and Xu, H. (2024). Designs for Order-of-Addition Screening Experiments. Statistica Sinica, 34(1), 399--419. https://doi.org/10.5705/ss.202021.0410
74. Tian, Y. and Xu, H. (2024). Stratification Pattern Enumerator and its Applications. Journal of the Royal Statistical Society Series B: Statistical Methodology, 86(2), 364-385.
75. Zhu, L., Man, C.-W., Harrison, R. E. S., Wu, Z., Limsakul, P., Peng, Q., Hashimoto, M., Mamaril, A. P., Xu, H., Liu, L., and Wang, Y. (2024). Engineering a Programmed Death-Ligand 1-Targeting Monobody Via Directed Evolution for SynNotch-Gated Cell Therapy. ACS Nano, 18 (11), 8531-8545.
76. Vazquez, A. R. and Xu, H. (2024). An integer programming algorithm for constructing maximin distance designs from good lattice point sets. Statistica Sinica, 34(3), 1347-1366.
77. Shi, C. and Xu, H. (2024). A Projection Space-Filling Criterion and Related Optimality Results. Journal of the American Statistical Association, 119(548), 2658-2669.

78. Stokes, Z., Wong, W. K., and Xu, H. (2024). Metaheuristic Solutions to Order-of-Addition Design Problems. Journal of Computational and Graphical Statistics, 33(3), 1006-1016.

79. Yuan, R., Yin, Y., Xu, H., and Liu, M.-Q. (2025). A Construction Method for maximin L1-distance Latin hypercube designs. Statistica Sinica, 35(1), 249-272.

80. Khan, Z. A., Song, S.-S., Xu, H., Ahmad, M. , Wang, A., Abdullah, A., Jiang, L.,and Ding, X. (2025). Elimination of Intracellular Microbes using Drug Combination Therapy and Unveiling Survival Mechanism of Host Cells upon Microbial Invasion. International Journal of Antimicrobial Agents, 107471.
81. Tian, Y. and Xu, H. (2025+). A Stratified L2-Discrepancy and its Applications. Journal of the Royal Statistical Society Series B: Statistical Methodology, published: 10 September 2025.

• Book chapters
1. Xu, H. (2015). Nonregular factorial and supersaturated designs. In Handbook of Design and Analysis of Experiments, eds A. Dean, M. Morris, J. Stufken and D. Bingham, Chapman and Hall/CRC, Series: Chapman & Hall/CRC Handbooks of Modern Statistical Methods, 339-370.

• Manuscripts submitted for publication or in preparation
• Onyambu, S. and Xu, H. (2025+). Tuning Differential Evolution Algorithm for Constructing Uniform Projection Designs.
• Shi, C., Tian, Y. and Xu, H. (2025+). Results on Large Strong Orthogonal Arrays of Strength Three.
• Huang, J.-W. and Xu, H. (2025+). Models for order-of-addition screening experiments.

• Miscellaneous
1. Cao, H. and Xu, H. (1990). Modulo-Period Sequence of Numbers, in Mathematical Olympiad in China, edited by Chinese Mathematical Olympiad Committee, Hunan Eduation Publishing House, 50-71. [Special edition for the 31st International Mathematical Olympiad (IMO) held in Beijing 1990].
2. Cao, H. and Xu, H. (1992). Periodic Sequences. University of Science and Technology of China, China (in Chinese).
3. Xu, H. (1997). Optimum Criteria and Optimum Designs in Experimental Design. Ph.D. thesis, Nankai University (in Chinese).
4. Xu, H. (2001). Optimal Factor Assignment for Asymmetrical Fractional Factorial Designs: Theory and Applications. Ph.D. thesis, University of Michigan, Ann Arbor.
5. Berk, R. A. and Xu, H. (2003). Comment on "Principal Stratification Approach to Broken Randomized Experiments: A Case Study of School Choice Vouchers in New York City" by J. Barnard, C. E. Frangakis, J. L. Hill and D. B. Rubin, Journal of the American Statistical Association, 98, 318-320.
6. Xu, H. (2006), Review of "Discovering Knowledge in Data: An Introduction to Data Mining'' by D. T. Larose, Journal of Statistical Software, 16, Book Review 1.
7. Xu, H. (2006), Review of "Design and Analysis of Experiments, Volume 2, Advanced Experimental Design" by K. Hinkelmann and O. Kempthorne, Technometrics, 48, 571.
8. Groemping, U, Amarov, B, and Xu, H. (2014), DoE.base: Full factorials, orthogonal arrays and base utilities for DoE packages. R Package DoE.base.

Supplements

• Supplement to Xu (2002, Technometrics, 44, 356-368): Algorithms: C source code and S source code. See Library of Orthogonal Arrays by Neil J. A. Sloane, a list of orthogonal arrays managed by Warren F. Kuhfeld at SAS, and complete series of non-isomorphic orthogonal arrays by Pieter Eendebak and Eric Schoen.
• Supplement to DX Random Number Generators [Deng and Xu (2003, ACM TOMACS, 13, 299-309)]
• Online catalogue of three-level regular fractional factorial designs [Xu (2005, Metrika, 62, 259-281)]
• A list of optimal multi-level supersaturated designs [supplement to Xu and Wu (2005, Annals of Statistics, 33, 2811-2836.)]
• Xu, H. (2009). Algorithmic Construction of Efficient Fractional Factorial Designs With Large Run Sizes. Technometrics, 51, 262-277.

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Last updated on September 2025.