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Liang Baosheng

Assistant professor
liangbs@hsc.pku.edu.cn
Xueyuan Road 38, Haidian District, Beijing, China
Peking University

Personal profile

Education experience

08/2016 - 04/2018 The University of Hong Kong, Postdoc in Biostatistics

09/2013 - 08/2014 University of North Carolina at Chapel Hill, Joint Training Ph.D in Biostatistics.

09/2012 - 06/2016 Beijing Normal University, Ph.D. in Probability Theory & Mathematical Statistics

09/2009 - 07/2012 Beijing Normal University, M.S. in Probability Theory & Mathematical Statistics

09/2005 - 06/2009 Qingdao University, B.S. in Mathematics and applied mathematics

Work experience

12/2014 – 12/2015 Columbia University, Department of Biostatistics, Part-time Staff Associate Statistics.

09/2014 – 11/2014 University of North Carolina at Chapel Hill, Department of Biostatistics, Research Assistant.

Main research directions

Biostatistics, Survival analysis, Semiparametric model, Recurrent-event data analysis, Robust statistics, Incomplete data analysis.

Representative scientific research projects

1. 2020.01-2022.12，Research on Semiparametric Efficient Approaches for Regression Analysis of Mixed Recurrent Event Data with Applications in the Study of Medication Adherence，National Natural Science Foundation of China，In charge.

2. 2020.01-2021.12，Research on Survival Analysis Method of Incomplete Family Data with Applications in Prevention of Alzheimer's Disease，Beijing Natural Science Foundation，In charge.

10 representative papers

1. Jin, S., Qin, D., *Liang, B.S, Zhang, L., Wei, X., Wang, Y., Zhuang, B., Zhang, T., Yang, Z., Cao, Y., Jin, S., Yang, P., Jiang, B., Rao, B., Shi, H., Lu*, Q. (2022). Machine learning predicts cancer-associated deep vein thrombosis using clinical available variables. International Journal of Medical Informatics. 161(2022)104733.

2. Zhang, Y., La, B., *Liang, B. S., Gu, Y. C. (2021) Treatment-Related Adverse Events with PD-1 or PD-L1 Inhibitors: A Systematic Review and Meta-Analysis. Life, 11, 1277. https:// 10.3390/ life11111277.

3. Jiang, Q., Xia, Y., and *Liang, B.S. (2021). Matching Distributions for Survival Data. Canadian Journal of Statistics. https://doi.org/10.1002/cjs.11641.

4. Liang, B.S., Wu, P., Tong, X. & *Qiu, Y. (2020). Regression and subgroup detection for heterogeneous samples, Computational Statistics. 35, 1853–1878.

5. Qiu YP, and *Liang BS (2019). Robust logistic regression of family data in the presence of missing genotypes. Journal of Applied Statistics. 46 (5): 926-945.

6. Liang BS, *Wang YJ, and Zeng DL (2018). Semiparametric Transformation Models with Multi-level Random Effects for Correlated Disease Onset in Families. Statistica Sinica. 29 (4): 1851-1871.

7. Li B, Liang BS, Tong XW and *Sun JG (2018). Rank Estimation of Partially Linear Transformation Models with Censored Data. Statistica Sinica. 29 (4): 1963-1975.

8. *Liang BS, Tong X, Zeng DL and Wang YJ (2017). Semiparametric Regression Analysis of Repeated Current Status Data. Statistica Sinica, 27 (3): 1079-1100.

9. *Wang YJ, Liang BS, Tong XW, Marder K, Bressman S, Orr-urtreger A, Giladi N and Zeng DL (2015). Efficient Estimation of Nonparametric Genetic Risk Function with Censored Data. Biometrika, 102 (3): 515-532.

10. *Liang BS, Tong XW, and Hu T (2015). Spline-based Sieve Estimation in Monotone Constrained Varying-coefficient Partially Linear EV Model. Statistics and Probability Letters, 103:169-175.