Jiwei Zhao, PhD

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The group has made significant contributions to the field and has successfully published the work in renowned (bio)statistical journals and top-tier machine learning conferences. The publications include prestigious journals like the Journal of the American Statistical Association, Journal of the Royal Statistical Society: Series B (Statistical Methodology), Annals of Statistics, Biometrika, Annals of Applied Statistics, and Biometrics. Furthermore, the group has also presented the findings at esteemed machine learning conferences, notably the International Conference on Machine Learning (ICML), the International Conference on Learning Representation (ICLR).

The publications are all listed below by year. The full publication list is also available from Dr. Zhao's Google Scholar.


      2025 and after

    1. Wang, L., Ma, Y. and Zhao, J. (2025). Borrowing information from an unidentifiable model: Guaranteed efficiency gain with a dichotomized outcome in the external data.

    2. Ghosh, T., Yu, M. and Zhao, J. (2025). Efficient estimation of average treatment effect on the treated under endogenous treatment assignment.

    3. Miao, X., Zhao, J. and Kang, H. (2025). Transfer learning between US presidential elections: How should we learn from a 2020 ad campaign to inform 2024 ad campaigns?

    4. Miao, J., Miao, X., Wu, Y., Zhao, J. and Lu, Q. (2025). Assumption-lean and data-adaptive post-prediction inference.

    5. Tian, Q., Zeng, D. and Zhao, J. (2025). Semiparametrically efficient approach for regression analysis with missing response and a hypothesis testing procedure for the missing data mechanism. Statistica Sinica.

    6. Tian, Q. and Zhao, J. (2025). Efficient and model-agnostic parameter estimation under privacy-preserving post-randomization data. Canadian Journal of Statistics.

    7. Shetty, S., Ma, Y. and Zhao, J. (2025). Robust estimation under a semiparametric propensity model for nonignorable missing data. Electronic Journal of Statistics.

    8. Yu, A. and Zhao, J. (2025). Counterfactual slopes and their applications in social stratification. Sociological Methodology.

    9. Lee, S., Ma, Y. and Zhao, J. (2025). Doubly flexible estimation under label shift. Journal of the American Statistical Association. In press.
      [GitHub Replication File]

    10. Yan, Y., Kim, J., Nejad-Davarani, S., Dong, M., Hurst Jr., N., Zhao, J. and Glide-Hurst, C. (2025). Deep learning-based synthetic CT for low field brain MR-Guided radiation therapy. International Journal of Radiation Oncology, Biology, Physics. In press.

      11. 2024

    11. Deng, S., Ning, Y., Zhao, J. and Zhang, H. (2024). Optimal and safe estimation for high-dimensional semi-supervised learning. Journal of the American Statistical Association. 119: 2748--2759.
      [GitHub Replication File]

    12. Feng, H., Duan, J., Ning, Y. and Zhao, J. (2024). Test of significance for high-dimensional thresholds with application to individualized minimal clinically important difference. Journal of the American Statistical Association. 119: 1396--1408.
      [GitHub Replication File]

    13. Miao, J., Wu, Y., Sun, Z., Miao, X., Lu, T., Zhao, J. and Lu, Q. (2024). Valid inference for machine learning-assisted genome-wide association studies. Nature Genetics. 56: 2361--2369.

    14. Kim, H., Zhang, X., Zhao, J. and Tian, Q. (2024). ReTaSA: A Nonparametric Functional Estimation Approach for Addressing Continuous Target Shift. The Twelfth International Conference on Learning Representations (ICLR).
      [GitHub Replication File]

    15. Xu, T. and Zhao, J. (2024). Relaxed doubly robust estimation in causal inference. Statistical Theory and Related Fields. 8: 69--79.

    16. Ghosh, T., Yu, M. and Zhao, J. (2024). A selective review on conditional density estimation. Statistics and Its Interface. 17: 549--564.

    17. Zhao, J., Zhou, Z. and Bisson, L. (2024). An asymptotically normal representation for the minimal clinically important difference under a nonconvex surrogate loss. Statistics and Its Interface. 17: 591--603.

    18. Summerfield, N., Morris E., Banerjee, S., He, Q., Ghanem, A., Zhu, S., Zhao, J., Dong, M. and Glide-Hurst, C. (2024). Enhancing precision in cardiac segmentation for MR-Guided radiation therapy through deep learning. International Journal of Radiation Oncology, Biology, Physics. 120: 904--914.

      19. 2023

    19. Guo, A., Zhao, J. and Nabi, R. (2023). Sufficient identification conditions and semiparametric estimation under missing not at random mechanisms. Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI). PMLR 216: 777--787.

    20. Tian, Q., Zhang, X. and Zhao, J. (2023). ELSA: Efficient label shift adaptation through the lens of semiparametric models. Proceedings of the 40th International Conference on Machine Learning (ICML). PMLR 202: 34120--34142.
      [GitHub Replication File]

    21. Shetty, S., Ma, Y. and Zhao, J. (2023). The pursuit of efficiency versus robustness: A learning experience from analyzing a semiparametric nonignorable propensity score model. Observational Studies. 9: 97--104.

    22. Fernandes-Taylor, S., Zhao, J. and Francis, D. (2023). New directions for improving the minimal clinically important difference in patient-reported outcome measures for use in clinical care and research. JAMA Otolaryngology-Head & Neck Surgery. 149: 276--277.

      23. 2022

    23. Zhao, J. and Ma, Y. (2022). A versatile estimation procedure without estimating the nonignorable missingness mechanism. Journal of the American Statistical Association. 117: 1916-1930.

    24. Feng, H., Ning, Y. and Zhao, J. (2022). Nonregular and minimax estimation of individualized thresholds in high dimension with binary responses. Annals of Statistics. 50: 2284-2305.

    25. Li, M., Ma, Y. and Zhao, J. (2022). Efficient estimation in a partially specified nonignorable propensity score model. Computational Statistics and Data Analysis. 174: 107322.

    26. Zhao, J. (2022). Comment on “Assumption-lean inference for generalised linear model parameters” by Vansteelandt, S. and Dukes, O. Journal of the Royal Statistical Society: Series B (Statistical Methodology). 84: 725-726. [paper discussion]

    27. Fernandes-Taylor, S., Damico-Smith, C., Arroyo, N., Wichmann, M., Zhao, J., Feurer, I. and Francis, D. for the CoPE Collaborative (2022). Multicenter development and validation of the vocal cord paralysis experience (CoPE), a patient-reported outcome measure for unilateral vocal fold paralysis-specific disability. JAMA Otolaryngology-Head & Neck Surgery. 148: 756--763.

    28. Greyner-Almeida, H., Fard, A., Chen, C., Zhao, J. and Patel, S. (2022). A portable, low-cost practice model for microsurgical skills training. International Ophthalmology. 42: 2323--2333.

    29. Bisson, L., Kluczynski, M., Wind, W., Fineberg, M., Bernas, G., Rauh, M., Marzo, J., Zhou, Z. and Zhao, J. (2022). Isolated arthroscopic partial meniscectomy is more effective at improving meniscal symptoms in comparison with mechanical symptoms in patients with concomitant untreated chondral lesions. Arthroscopy. 38: 489-497.

    30. Bisson, L., Kluczynski, M., Wind, W., Fineberg, M., Bernas, G., Rauh, M., Marzo, J., Scrivens, B., Connaughton, A., Zhou, Z. and Zhao, J. (2022). Better outcomes but no difference in joint space narrowing at five years among patients without unstable chondral lesions versus those with unstable chondral lesions (left in situ) at the time of arthroscopic partial meniscectomy. Arthroscopy. 38: 936-944.

      31. 2021

    31. Fang, F., Zhao, J., Ahmed, S.E. and Qu, A. (2021). A weak-signal-assisted procedure for variable selection and statistical inference with an informative subsample. Biometrics. 77: 996-1010.

    32. Mickevicius, N., Kim, J., Zhao, J., Morris, Z., Hurst Jr., N. and Glide-Hurst, C. (2021). Toward magnetic resonance fingerprinting for low-field MR-guided radiation therapy. Medical Physics. 48: 6930–6940.

    33. Bisson, L., Kluczynski, M., Wind, W., Fineberg, M., Bernas, G., Rauh, M., Marzo, J., Scrivens, B., Connaughton, A., Zhou, Z. and Zhao, J. (2021). Observation versus debridement of unstable chondral lesions during partial meniscectomy: analysis of patient outcomes and degenerative joint disease at 5 years in the chondral lesions and meniscus procedures (ChAMP) randomized controlled trial. Journal of Bone & Joint Surgery. 103: 1569-1577.

    34. Myneni, A., Giovino G., Millen, A., LaMonte, M., Wactawski-Wende J., Neuhouser, M., Zhao, J., Shikany, J. and Mu, L. (2021). Indices of diet quality and risk of lung cancer in the Women's Health Initiative Observational Study. Journal of Nutrition. 151: 1618-1627.

    35. Gannon, E., Higham, D., Gardner, B., Nan, N., Zhao, J. and Bisson, L. (2021). Changes in neuromuscular status across a season of professional men's ice hockey. Journal of Strength and Conditioning Research. 35: 1338-1344.

    36. Gordon, J., LaMonte, M., Zhao, J., Genco, R., Cimato, T., Hovey, K. and Wactawski-Wende, J. (2021). Association between serum inflammatory biomarkers and incident hypertension among postmenopausal women in the Buffalo OsteoPerio study. Journal of Human Hypertension. 35: 791-799.

      37. 2020

    37. Zhou, Z., Zhao, J. and Bisson, L. (2020). Estimation of data adaptive minimal clinically important difference with a nonconvex optimization procedure. Statistical Methods in Medical Research. 29: 879–893.

    38. Zhao, J. and Chen, C. (2020). A nuisance-free inference procedure accounting for the unknown missingness with application to electronic health records. Entropy. 22: 1154.

    39. Yang, Y., Zhao, J., Wilding, G., Kluczynski, M. and Bisson, L. (2020). Stability enhanced variable selection for a semiparametric model with flexible missingness mechanism and its application to the ChAMP study. Journal of Applied Statistics. 47: 827–843.

    40. Zhou, Z., Zhao, J. and Kluczynski, M. (2020). Interval estimation for minimal clinically important difference and its classification error via a bootstrap scheme. Statistical Theory and Related Fields. 4:135–145.

    41. Zhao, J. (2020). A penalized likelihood approach for statistical inference in a high-dimensional linear model with missing data. The 37th ICML (International Conference on Machine Learning) Workshop: The Art of Learning with Missing Values. [refereed conference]

    42. Matthews, J., Wang, J., Zhao, J., Kluczynski, M. and Bisson, L. (2020). The influence of suture materials on the biomechanical behavior of suture-meniscal specimens: a comparative study in a porcine model. Knee Surgery & Related Research. 32: 42.

    43. Dighe, S., Zhao, J., Steffen, L., Mares, J., Meuer, S., Klein, B., Klein, R. and Millen, A. (2020). Diet patterns and the incidence of age-related macular degeneration in the Atherosclerosis Risk in Communities (ARIC) study. British Journal of Ophthalmology. 104: 1070–1076.

    44. Jacobs, D., Ochs-Balcom, H., Noyes, E., Zhao, J., Murphy, T., Sethi, S. and Pu, C. (2020). Impact of pseudomonas aeruginosa isolation on mortality and outcomes in an outpatient COPD cohort. Open Forum Infectious Diseases. 7: ofz546.

      45. 2019

    45. Han, P., Kong, L., Zhao, J. and Zhou, X. (2019). A general framework for quantile estimation with incomplete data. Journal of the Royal Statistical Society: Series B (Statistical Methodology). 81: 305–333.

    46. Zhao, J. and Chen, C. (2019). Estimators based on unconventional likelihoods with nonignorable missing data and its application to a children’s mental health study. Journal of Nonparametric Statistics. 31: 911–931.

    47. Gordon, J., LaMonte, M., Genco, R., Zhao, J., Li, L., Hovey, K., Tsompana, M., Buck, M., Andrews, C., McSkimming, D., Zheng, W., Sun, Y. and Wactawski-Wende, J. (2019). Is the oral microbiome associated with blood pressure in older women? High Blood Pressure & Cardiovascular Prevention. 26: 217–225.

    48. Bisson, L., Phillips, P., Matthews, J., Zhou, Z., Zhao, J., Wind, W., Fineberg, M., Bernas, G., Rauh, M., Marzo, J. and Kluczynski, M. (2019). Association between bone marrow lesions, chondral lesions, and pain in patients without radiographic evidence of degenerative joint disease who underwent arthroscopic partial meniscectomy. Orthopaedic Journal of Sports Medicine. 7: 2325967119830381.

    49. Sharma, S., Wactawski-Wende, J., LaMonte, M., Zhao, J., Slade, G., Bair, E., Greenspan, J., Fillingim, R., Maixner, W. and Ohrbach, R. (2019). Incident injury is strongly associated with subsequent incident temporomandibular disorder: Results from the OPPERA study. Pain. 160: 1551–1661.

    50. Touban, B., Pavlesen, S., Smoak, J., Sayegh, M.,Wang, J., Zhao, J. and Anders, M. (2019). Decreased lean psoas cross-sectional area is associated with increased 1-year all-cause mortality in male elderly orthopaedic trauma patients. Journal of Orthopaedic Trauma. 33: e1–e7.

    51. Gordon, J., LaMonte, M., Zhao, J., Genco, R., Cimato, T., Hovey, K., Allison, M., Mouton, C. and Wactawski-Wende, J. (2019). Association of periodontal disease and edentulism with hypertension risk in postmenopausal women. American Journal of Hypertension. 32: 193–201.

      52. 2018

    52. Zhao, J. and Ma, Y. (2018). Optimal pseudolikelihood estimation in the analysis of multivariate missing data with nonignorable nonresponse. Biometrika. 105: 479–486.

    53. Zhang, H., Liu, D., Zhao, J. and Bi, X. (2018). Modeling hybrid traits for comorbidity and genetic studies of alcohol and nicotine co-dependence. Annals of Applied Statistics. 12: 2359–2378.

    54. Zhao, J., Yang, Y. and Ning, Y. (2018). Penalized pairwise pseudo likelihood for variable selection with nonignorable missing data. Statistica Sinica. 28: 2125–2148.

    55. Fang, F., Zhao, J. and Shao, J. (2018). Imputation-based adjusted score equations in generalized linear models with nonignorable missing covariate values. Statistica Sinica. 28: 1677–1701.

    56. Chen, C., Zhao, J., Miecznikowski, J. and Markatou, M. (2018). A comparison of high-dimensional variable selection methods with missing covariates in a prostate cancer study. Communications in Statistics - Case Studies, Data Analysis and Applications. 4: 82–95.

    57. Zhao, J. (2018). Statistical methods without estimating the missingness mechanism: A discussion of “Statistical inference for nonignorable missing data problems: A selective review” by Niansheng Tang and Yuanyuan Ju. Statistical Theory and Related Fields. 2: 143–145. [invited discussion]

    58. Gordon, J., LaMonte, M., Genco, R., Zhao, J., Cimato, T., Hovey, K. and Wactawski-Wende J. (2018). Association of clinical measures of periodontal disease with blood pressure and hypertension among postmenopausal women. Journal of Periodontology. 89: 1193–1202.

    59. Banack, H., Genco, R., LaMonte, M., Millen, A., Buck, M., Sun, Y., Andrews, C., Hovey, K., Tsompana, M., McSkimming, D., Zhao, J., and Wactawski-Wende, J. for the OsteoPerio Study Group. (2018). Cohort profile: the Buffalo OsteoPerio Microbiome Prospective Cohort Study. BMJ Open. 8: e024263.

    60. Jacobs, D., Ochs-Balcom, H., Zhao, J., Murphy, T. and Sethi, S. (2018). Lower airway bacterial colonization patterns and species-specific interactions in chronic obstructive pulmonary disease. Journal of Clinical Microbiology. 56: e00330-18.

    61. Jacobs, D., Noyes, E., Zhao, J., Gibson, W., Murphy, T., Sethi, S. and Ochs-Balcom, H. (2018). Early hospital readmissions after an acute exacerbation of chronic obstructive pulmonary disease in the nationwide readmissions database. Annals of the American Thoracic Society. 15: 837–845.

    62. Bisson, L., Kluczynski, M., Wind, W., Fineberg, M., Bernas, G., Rauh, M., Marzo, J., Zhou, Z. and Zhao, J. (2018). How does the presence of unstable chondral lesions affect patient outcomes after partial meniscectomy?: the chondral lesions and meniscus procedures (ChAMP) randomized controlled trial. American Journal of Sports Medicine. 46: 590–597.

      63. 2017

    63. Zhao, J. (2017). Reducing bias for maximum approximate conditional likelihood estimator with general missing data mechanism. Journal of Nonparametric Statistics. 29: 577–593.

    64. Zhao, J. and Shao, J. (2017). Approximate conditional likelihood for generalized linear models with general missing data mechanism. Journal of System Science and Complexity. 30: 139–153.

    65. Xu, J., Shan, G., Amei, A., Zhao, J., Young, D, and Clark, S. (2017). A modified Friedman test for randomized complete block designs. Communications in Statistics - Simulation and Computation. 46: 1508–1519.

    66. Zhao, J. and Yang, Y. (2017). Tuning parameter selection in the LASSO with unspecified propensity. In New Advances in Statistics and Data Science, Springer, pp. 109–125. [refereed book chapter]

    67. Kluczynski, M., Marzo, J., Wind, W., Fineberg, M., Bernas, G., Rauh, M., Zhou, Z., Zhao, J. and Bisson, L. (2017). The effect of body mass index on clinical outcomes in patients without radiographic evidence of degenerative joint disease after arthroscopic partial meniscectomy. Arthroscopy-The Journal of Arthroscopic and Related Surgery. 33: 2054–2063.

    68. Sheppard, A., Chen, G., Manohar, S., Ding, D., Hu, B., Sun, W., Zhao, J. and Salvi, R. (2017). Prolonged low-level noise-induced plasticity in the peripheral and central auditory system of rats. Neuroscience. 359: 159–171.

    69. Bisson, L., Kluczynski, M., Wind, W., Fineberg, M., Bernas, G., Rauh, M., Marzo, J., Zhou, Z. and Zhao, J. (2017). Patient outcomes after debridement of unstable chondral lesions during partial meniscectomy: the chondral lesions and meniscus procedures (ChAMP) randomized controlled trial. Journal of Bone & Joint Surgery. 99: 1078–1085.

    70. Meaney, C., Beccari, M., Yang, Y. and Zhao, J. (2017). Systematic review and metaanalysis of patiromer and sodium zirconium cyclosilicate: a new armamentarium for the treatment of hyperkalemia. Pharmacotherapy. 37: 401–411.

      71. 2016 and before

    71. Zhao, J. and Zhang, H. (2016). Modeling multiple responses via bootstrapping margins with an application to genetic association testing. Statistics and Its Interface. 9: 47–56.

    72. Zhao, J. and Shao, J. (2015). Semiparametric pseudo-likelihoods in generalized linear models with nonignorable missing data. Journal of the American Statistical Association. 110: 1577–1590.

    73. Zhao, J., Cook, R. and Wu, C. (2015). Multiple imputation for the analysis of incomplete compound variables. Canadian Journal of Statistics. 43: 240–264.

    74. Shao, J. and Zhao, J. (2013). Estimation in longitudinal studies with nonignorable dropout. Statistics and Its Interface. 6: 303–313.

    75. Shao, J., Zhang, S., Zhao, J. and Chiang, A. (2012). Multiple testing for a combination drug with two study endpoints. Statistics in Medicine. 31: 1779–1790.