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周岭

周岭

  • 周岭

  • 系别:统计研究中心

  • 职称:副教授

  • 办公电话:28

  • Email:zhouling@swufe.edu.cn

  • 教师简介

  • 研究成果

  • 学术活动

  • 教授课程

  • 研究兴趣:

    Big Data Analytics, Data Integration, Longitudinal Data Analysis, Post-selection Inference, Survival Analysis, Transformation Model, Variance-Covariance Structure.

    教育经历

    2015.9-2018.9 博士后 美国密歇根大学

    2011.9-2014.12 博士 西南财经大学

    2004.9-2011.6 本科/硕士 四川大学

    所获荣誉:

    2017年荣获钟家庆数学奖

  • 研究成果:

    16. Zhou, L., Li, H., Lin, H., and Song, P. X. K. (2018). Evaluation of functional covariateenvironment interaction in the Cox model.Canadian Journal of Statistics, accepted.

    15. Li, Y., Wang, S., Song, P. X. K., Wang, N.,Zhou, L., and Zhu, J. (2018). Doubly regularized estimation and selection in linear mixed-effects models for high-dimensional longitudinal data.Statistics and Its Interface, to appear.

    14. Tang, L., Chaudhuri, S., Bagherjeiran, A., andZhou, L.(2018). Learning large scale ordinal ranking model via divide-and-conquer technique.Companion of the Web Conference2018, 1901-1909, International World Wide Web Conference Steering Committee.

    13. Tang, L.,Zhou, L., and Song, P. X. K. (2018). Fusion learning algorithm to combine partially heterogeneous Cox models.Computational Statistics, to appear.

    12. Jansen, E. C.,Zhou, L.*, Song, P. X. K., Sanchez, B. N., Mercado, A., Hu, H., Solano, M., Peterson, K. E., and Tellez-Rojo M. M. (2018). Prenatal lead exposure in relation to age at menarche: results from a longitudinal study in Mexico City.Journal of Developmental Origins of Health and Disease(accepted). (* Co-first author). DOI: 10.1017/S2040174418000223.

    11. Jansen, E. C.,Zhou, L., Perng, W., Song, P. X. K., Tellez-Rojo, M. M., Mercado, A., Peterson, K. E., and Cantoral, A. (2018). Vegetable and lean proteins-based and processed meat and refined grains pattern-based dietary patterns in early childhood are associated with pubertal timing in a sex-specific manner: A prospective study of children from Mexico City.Nutrition Research(accepted). DOI: 10.1016/j.nutres.2018.04.021.

    10. Lin, H., Zhou, F., Wang, Q.,Zhou, L., and Qin, J. (2018). Robust and efficient estimation for the treatment effect in causal inference and missing data problems.Journal of Econometrics,205,363-380.

    9. Zhou, L., Lin, H., and Liang, H. (2017). Efficient estimation of the nonparametric mean and covariance functions for longitudinal and sparse functional data.Journal of the American Statistical Association(accepted). DOI:10.1080/01621459.2017.1356317.

    8. Lin, H.,Zhou, L., and Wang, B. (2017). Generalized partial linear models with unknown link and unknown baseline functions for longitudinal data.Statistica Sinica, 27, 1281{1298.

    7. Zhou, L., Tang, L., Song, A. T., Cibrik, D. M., and Song, P. X. K. (2017). A LASSO method to identify protein signature predicting post-transplant renal graft survival.Statistics in Biosciences, 9(2), 431-452.

    6. Zhou, L., Lin, H., and Lin Y. C. (2016). Education, intelligence, and well-being: Evidence from a semiparametric latent variable transformation model for multiple outcomes of mixed types.Social Indicators Research, 125(3), 1011-1033.

    5. Lin, H.,Zhou, L., Li, C., and Li, Y. (2014). Semiparametric transformation models for semicompeting survival data.Biometrics, 70, 599-607.

    4. Zhou, L., Lin, H., Song, X. and Li, Y. (2014). Selection of latent variables for multiple mixed-outcome models.Scandinavian Journal of Statistics, 41, 1064-1082.

    3. Lin, H.,Zhou, L., and Zhou, X. (2014). Semiparametric regression analysis of longitudinal skewed data.Scandinavian Journal of Statistics, 41, 1031-1050.

    2. Lin, H.,Zhou, L., Elashof, R. M., and Li, Y. (2014). Semiparametric latent variable transformation models for multiple mixed outcomes.Statistica Sinica, 24, 833-854.

    1. Lin, H.,Zhou, L., Peng, H., and Zhou, X. H. (2011). Selection and combination of biomarkers using ROC method for disease classification and prediction.Canadian Journal of Statistics, 39, 324-343.