详情参见个人主页：Homepage of Jinhong Li

生存分析, 假设检验, 高维数据, 图像数据

联合培养博士研究生，2023.11-2024.11，统计学，美国，加州大学河滨分校

博士研究生, 2021.9-2025.6, 统计学, 华东师范大学, 博士

浙江工商大学统计与数据科学学院, 应用统计系, 讲师, 2025.9-至今

• Li, J., Liu, J.*, You, J., Zhang, R. Two-Sample Robust Nonparametric Tests for Matrix-Valued Data: a Double Projection-Averaging Method.

• Li, J., Liu, J.*, Zhang, R. Conditional Independence Testing for Right-censored Data via Counting Process and Kernel Embedding Approach.

• Li, J., Ma, S. Causal Inference of Treatment Effects using Neural Networks with A Diverging Number of Confounders. Working paper

• Li, J., Liu, J.*, Ma, S., Zhang, R. Testing Independence in High-Dimensional Survival Data Using Conditional Moment Restrictions Approach.

• Liu, J., Zhang, Y., Li, J.*. Sufficient Dimension Reduction via Inverse Conditional Mean or Variance Independence.

• Zhu, H., Cai, S., Hu, Z., Li, J.* . Spatially Varying Coefficient Additive Model with An Application to Brain Imaging Data.

• Li, J., Liu, J.*, You, J., Zhang, R. (2025). SID: A Novel Class of Nonparametric Tests of Independence for Censored Outcomes. Bernoulli. [Accepted, Code]

• Liu, J.*, Li, J., Zhang, R. (2022). K-CDFs: A Nonparametric Clustering Algorithm via Cumulative Distribution Function. Journal of Computational and Graphical Statistics, 32(1), 304–318. [PDF]

• Li, J., Liu, J., Zhang, R*. (2022). Estimating restricted mean treatment effects with additive-multiplicative hazards models. Journal of Nonparametric Statistics, 34(4), 1015–1035. [PDF, Code]

• Pei, Y.*, Li, J. (2020). Estimating the difference of restricted mean life under dependent censor. SCIENTIA SINICA Mathematica, 50(3), 405–422. [PDF]