一、个人基本情况

姓名：梁晋雯

性别：女

职称：讲师

所在部门：数理统计研究所

二、主要研究方向

张量回归、分位数回归、统计优化

三、教育与工作经历

2022.09 至今，讲师，suncity太阳新城，suncitygroup太阳新城

2017.09-2022.06，中国人民大学，统计学，博士

2013.09-2017.06，北京交通大学，信息与计算科学，学士

四、主要科研项目

五、学术成果与荣誉

发表的论文：

1. Liang, J., and Tian, M. (2025). Sequential thresholded quantile estimator for sparse regression. Communications in Statistics - Theory and Methods, https://doi.org/10.1080/03610926.2025.2503310.

2. Liang, J., Tian, M., and Rong, Y. (2024). Non parametric maximin aggregation for data with inhomogeneity. Communications in Statistics - Theory and Methods, 53(22), 8109–8126.

3. Liang, J., and Tian, M. (2024). Imputed quantile vector autoregressive model for multivariate spatial–temporal data. Statistical Analysis and Data Mining, 17, e11658.

4. Liang, J., Härdle, W. K., and Tian, M. (2023). Imputed quantile tensor regression for near-sited spatial-temporal data. Computational Statistics & Data Analysis, 182, 107713.

5. Shu, Y., Liang, J., Rong, Y., Fu, Z., and Yang, Y. (2023). A more accurate estimation with kernel machine for nonparametric spatial lag models. Spatial Statistics, 58, 100786.

6. Liang, J., and Tian, M. (2023). Imputed mean tensor regression for near-sited spatial temporal data. Journal of Applied Statistics, 51(6), 1057–1075.

7. Liang, J., and Tian, M. (2023). Sparse regression for low-dimensional time-dynamic varying coefficient models with application to air quality data, Journal of Applied Statistics, 50(6), 1378-1399.

8. Liang, J., Zhang, X., Wang, K., Tang, M., and Tian, M. (2022). Discovering dynamic models of COVID-19 transmission. Transboundary and emerging diseases, 69(4), e64–e70.

六、联系方式

地址：北京市朝阳区平乐园100号数理楼 436

E-mail：jinwen@bjut.edu.cn