教育经历

2012---2016，中国科学技术大学管理学院，统计学，学士

2016---2022，中国科学技术大学管理学院，统计学，博士

工作经历

2022---2024，中国科学技术大学管理学院，统计学，博士后

科研项目

中国博士后科学基金第73批面上资助，函数型线性回归模型中的假设检验，2023.9---2025.9，主持

合肥工业大学青年教师科研启动专项A，在线函数型数据降维理论方法及应用，2024.5---2025.5，主持

研究成果

[14] Xu, J., Zhao, Y., & Cheng, H. (2025). Online kernel sliced inverse regression. Computational Statistics & Data Analysis, 203, 108071.

[13] Yang, X., & Xu, J. (2024). Functional sufficient dimension reduction through distance covariance. Journal of Statistical Computation and Simulation, 1-22.

[12] Li, X., Xu, J., & Cheng, H. (2024). Functional sufficient dimension reduction through information maximization with application to classification. Journal of Applied Statistics, 1-43.

[11] Cui, W., Li, J., & Xu, J. (2024). Information consistency of dependent convolved Gaussian processes regression. International Journal of Wavelets, Multiresolution and Information Processing.

[10] 丁雨辰, 徐建军, & 崔文泉. (2024). 适用于稀疏隐式反馈数据的双重去偏协同过滤推荐算法. 计算机系统应用, 33(8), 145-154.

[9] Li, X., Xu, J., & Cheng, H. (2023). Functional data clustering via information maximization. Journal of Statistical Computation and Simulation, 93(16), 2982-3007.

[8] Cui, W., Xu, J., & Wu, Y. (2023). A new reproducing kernel‐based nonlinear dimension reduction method for survival data. Scandinavian Journal of Statistics, 50(3), 1365-1390.

[7] Cui, W., Zhao, Y., Xu, J., & Cheng, H. (2023). Federated sufficient dimension reduction through high-dimensional sparse sliced inverse regression. Communications in Mathematics and Statistics, 1-38.

[6] Xu, J., Cui, W., & Cheng, H. (2023). Online sparse sliced inverse reression for high-dimensional streaming data. International Journal of Wavelets, Multiresolution and Information Processing, 21(02), 2250055.

[5] Wang, Y., Cui, W., & Xu, J. (2023). Online confidence interval estimation for federated heterogeneous optimization. JUSTC, 53(11), 1103-1.

[4] Ma, Y., Li, Y., & Xu, J. (2023). Confidence intervals for high-dimensional multi-task regression. JUSTC, 53(4), 0403-1.

[3] Cui, W., He, X., Cheng, H., & Xu, J. (2022). Sufficient dimension reduction via distance covariance for survival data. International Journal of Wavelets, Multiresolution and Information Processing.

[2] Xu, J., & Cui, W. (2022). A new RKHS-based global testing for functional linear model. Statistics & Probability Letters, 182, 109277.

[1] 崔文泉, 张枫, & 徐建军. (2020). 一种基于核随机投影的集成分类方法. JOURNAL OF UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA, 50(7).