Liu Bin
Associate Professor
Statistics and Data Science
Academic Posts
2023.08—,Member of a Council,Branch of Statistics Cross-Science Research，Chinese Association for Applied Statistics
Journal Papers
| 1. | Xianru Wang, Bin Liu, Xinsheng Zhang, and Yufeng Liu. 2025. Efficient multiple change point detection and localization for high-dimensional quantile regression with heteroscedasticity. Journal of the American Statistical Association forthcoming 976-989.  |
| 2. | Zhi Yang, Liwen Zhang, Siyu Sun, and Bin Liu. 2025. Robust change point detection for high-dimensional linear models with tolerance for outliers and heavy tails. The Canadian Journal of Statistics 53(1) 1-20. |
| 3. | Bin Liu, Zhengling Qi, Xinsheng Zhang, and Yufeng Liu. 2024. Change point detection for high-dimensional linear models: A general tail-adaptive approach. Statistica Sinica forthcoming 1-40. |
| 4. | Haixu Ma, Zhuoyu Shi, Minjeong Kim, Bin Liu, Patrick J. Smith, Yufeng Liu, Guorong Wu, and Alzheimer's Disease Neuroimaging Initiative (ADNI). 2024. Disentangling sex-dependent effects of APOE on diverse trajectories of cognitive decline in Alzheimer’s disease. NeuroImage 292 1-19. |
| 5. | Bin Liu, Xinsheng Zhang, and Yufeng Liu. 2024. Simultaneous change point detection and identification for high dimensional linear models. Statistica Sinica forthcoming 1-40. |
| 6. | Xianru Wang, Bin Liu, Xinsheng Zhang, and Yufeng Liu. 2023. Efficient multiple change point detection for high-dimensional generalized linear models. The Canadian Journal of Statistics 51(2) 596-629. |
| 7. | Xianru Wang, Bin Liu, and Xinsheng Zhang. 2022. A computationally efficient and flexible algorithm for high dimensional mean and covariance matrix change point models. Journal of the Korean Statistical Society 51 1216-1246. |
| 8. | Bin Liu, Xinsheng Zhang, and Yufeng Liu. 2022. High dimensional change point inference: Recent developments and extensions. Journal of Multivariate Analysis 188 1-19. |
| 9. | Bin Liu, Xinsheng Zhang, and Yufeng Liu. 2021. Simultaneous change point inference and structure recovery for high dimensional gaussian graphical models. Journal of Machine Learning Research 22(1) 1-62. |
| 10. | Bin Liu, Cheng Zhou, Xinsheng Zhang, and Yufeng Liu. 2020. A unified data-adaptive framework for high dimensional change point detection. Journal of the Royal Statistical Society Series B-Statistical Methodology 82(4) 933-963. |
| 11. | Bin Liu, Cheng Zhou, and Xinsheng Zhang. 2019. A tail adaptive approach for change point detection. Journal of Multivariate Analysis 169 33-48. |
| 12. | Mingjuan Zhang, Chen Zhou, Yong He, and Bin Liu. 2018. Data-adaptive test for high-dimensional multivariate analysis of variance problem. Australian & New Zealand Journal of Statistics 60(4) 447-470. |
| 13. | Yong He, Xinsheng Zhang, Jiadong Ji, and Bin Liu. 2017. Joint estimation of multiple high-dimensional Gaussian copula graphical models. Australian & New Zealand Journal of Statistics 59(3) 289-310. |
Research Projects
2025.01—2028.12, Principal Investigator, Efficient Change-Point Inference for Relevant Structures of Ultra-High Dimensional Complex Data, National Natural Science Foundation of China
2024.04—2025.02, Principal Investigator, Commodity Data Intelligent Business Decision System, Shandong Zhuochuang Information Co. LTD
2024.01—2028.12, Member, Statistical Inference of Multi-source Heterogeneous Data based on Information Fusion and Migration, National Natural Science Foundation of China
2022.01—2024.12, Principal Investigator, Some Studies on Point Inference for High-Dimensional Regression Parameters, National Natural Science Foundation of China
2021.11—2022.06, Principal Investigator, Research on Commodity Price Forecasting Model, Shandong Zhuochuang Information Co. LTD
2020.01—2023.12, Member, Some Statistical Inference Problem for High-dimensional Big Data, National Natural Science Foundation of China
2018.01—2021.12, Member, Statistical Inference and Applications on Differential Models in the Big Data Era, National Natural Science Foundation of China
Academic Posts
2023.08—,Member of a Council,Branch of Statistics Cross-Science Research，Chinese Association for Applied Statistics
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