教师姓名：谢锦瀚

职    称：副教授

系    所：统计与数据科学系

主要研究领域：

统计机器学习：在线学习(Online learning); 迁移学习(Transfer learning); 联邦学习(Federate learning); 集成学习(Ensemble learning)

大规模复杂数据分析：高维数据(High dimensional data); 流数据分析(Streaming data); 隐私数据(Privacy data); 缺失数据(Missing data)

电子邮件：jinhanxie@ynu.edu.cn

个人主页：

https://www.researchgate.net/profile/Xie-Jinhan

https://scholar.google.com/citations?user=wxSqrpwAAAAJ&hl=en

教育背景：

2008.09 - 2012.06 上饶师范学院 数学与计算机科学学院，学士，数学与应用数学专业

2012.09 - 2015.06 37000gcom威尼斯 37000gcom威尼斯，硕士，概率论与数理统计

2015.09 - 2019.06 37000gcom威尼斯 37000gcom威尼斯，博士，统计学

工作经历：2017.04 - 2017.08; 2019.01 - 2019.06 香港中文大学， 统计系， 研究助理

2019.06-2012.06 香港中文大学，统计系，博士后

2021.01-2024.01 加拿大阿尔伯塔大学， 数学与统计科学系，博士后

2024.01-2024.12 美国北卡罗来纳大学教堂山分校，生物统计系， 博士后

代表性学术论著：（+ and * indicate equal contributions and corresponding author, respectively.）

1. Xie, J., Yan, X., Jiang, B., and Kong*, L. (2024). Statistical inference for smoothed quantile regression with streaming data. Journal of Econometrics, 105924.

2. Han#, D., Xie#, J., Liu*, J., Sun, L., Huang, J., Jiang, B., and Kong, L. (2024). Inference on high-dimensional single-index models with streaming data. Journal of Machine Learning Research, 25, 1-68.  

3. Qin, C., Xie, J., Li, T., and Bai*, Y. (2024). An adaptive transfer learning framework for functional classification. Journal of the American Statistical Association, accepted, in press.

4. Shi, E., Xie, J., Hu, S., Sun, K., Dai, H., Jiang, B., Kong*, L., and Li, L. (2024). Tracking full posterior in online Bayesian classification learning: a particle filter approach. Journal of Nonparametric Statistics, accepted, in press.

5. Dong, W., Xu, C., Xie, J., and Tang*, N. (2024). Tuning-free sparse clustering via alternating hard-thresholding. Journal of Multivariate Analysis, 203, 105330.

6. Kong, L., Luo, X., Xie, J., Zhu, L., and Zhu*, H. (2024). A functional nonlinear mixed effects modeling framework for longitudinal functional response. Electronic Journal of Statistics, 18, 1355-1393.

7. Xie, J., Ding, X, Jiang, B., Yan, X., and Kong*, L. (2024). High dimensional model averaging for quantile regression. The Canadian Journal of Statistics, 52, 618-635.

8. Yan, X., Xie, J., Tu, W., Jiang, B., and Kong*, L. (2024). Scalable inference for individual treatment effect. Statistics and Its Interface, 17, 413-423.

9. Lin#, Y., Xie#, J., Han, R., and Tang*, N. (2023). Post-selection inference of high-dimensional logisitic regression under case-control design. Journal of Business & Economic Statistics, 41, 624-635.

10. Yan, X., Wang, H., Zhou, Y., Yan, J., Wang, Y., Xie*, J., Yang, S., Zeng, Z., and Chen, X. (2022). Heterogeneous logistic regression for estimation of subgroup effects on hypertension. Journal of Biopharmaceutical Statistics, 32, 969-985.

11. Hu*, S., Al-Ani, J. A., Hughes, K. D., Denier, N., Konnikov, A., Ding, L., Xie, J., Yang, H., Tarafdar, M., Jiang, B., Kong, L., and Dai, H. (2022). Balancing gender bias in job advertisements with Text-level bias mitigation. Frontiers in Big Data, 5, 805713.

12. Ding, L., Yu, D., Xie, J., Guo, W., Hu, S., Liu, M., Kong*, L., Dai, H., Bao, Y., and Jiang, B. (2022). Word embeddings via causal inference: gender bias reducing and semantic information preserving. Proceedings of the Thirty-Sixth AAAI conference on Artificial Intelligence, 36, 11864-11872.

13. Tang, W., Xie, J., Lin, Y., and Tang*, N. (2022). Quantile correlation-based variable selection. Journal of Business & Economic Statistics, 40, 1081-1093.

14. Ding, X., Xie*, J., and Yan, X. (2021). Model averaging for composite quantile regressions with covariates missing at random. Journal of Statistical Computation and Simulation, 91, 2249-2275.

15. Yan, X., Wang, H., Wang, W., Xie*, J., Ren, Y., and Wang, X. (2021). Optimal model averaging forecasting in high-dimensional survival analysis. International Journal of Forecasting, 37, 1147-1155.

16. Xie, J., Yan, X., and Tang*, N. (2021). A model-averaging method for high-dimensional regression with missing responses at random. Statistica Sinica, 31, 1005-1026.

17. Xie, J., Lin*, Y., Yan, X., and Tang, N. (2020). Category-adaptive variable screening for ultra-high dimensional heterogeneous categorical data. Journal of the American Statistical Association, 115, 747-760.

18. Xie, J., Hao, M., Liu, W., and Lin*, Y. (2020). Fused variable screening for massive imbalanced data. Computational Statistics & Data Analysis, 141, 94-108.

19. Li, X., Tang*, N., Xie, J., and Yan, X. (2020). A nonparametric feature screening method for ultrahigh-dimensional missing data. Computational Statistics & Data Analysis, 142, 106828.

20. Yan, X., Tang*, N., Xie, J., Ding, X., and Wang, Z. (2018). Fused mean-variance filter for feature screening. Computational Statistics & Data Analysis, 122, 18-32.

获奖情况：

1. 唐年胜、赵普映、李会琼、谢锦瀚、唐安民, 高维缺失数据的统计推断，云南省人民政府，云南省自然科学奖一等奖，2023 年；

2. 云南省2021年优秀博士论文, 2021年

主要学术任职：

国际学术期刊:  Journal of the American Statistical Association, Statistics and Computing, NeurIPS, ICLR, Canadian Journal of Statistics, Computational Statistics and Data Analysis, Statistics in Medicine, Statistical Analysis and Data Mining, Statistics and Its Interface, Communications in Mathematics and Statistics等匿名审稿人。