代表性论文：
统计学：
[1] Chen Z., Leng C. Dynamic Covariance Models. Journal of the American Statistical Association, 111: 1196–1207, 2016.
[2] Chen Z., Tang M.-L., Gao W. A Profile Likelihood Approach for Longitudinal Data Analysis. Biometrics, 74: 220–228, 2018. (T1)
[3] Chen Z., Ning J., Shen Y., Qin J. Combining Primary Cohort Data with External Aggregate Information without
Assuming Comparability. Biometrics, 77: 1024–1036, 2021. (T1)
[4] Chen Z., Shen Y., Qin J., Ning J. Likelihood Adaptively Incorporated External Aggregate Information with Uncertainty for Survival Data. Biometrics, 80(4): ujae120, 2024. (T1)
[5] Jiang B., Chen Z., Leng C. Dynamic Linear Discriminant Analysis for High-dimensional Data. Bernoulli, 26:
1234–1268, 2020. (T1)
[6] Chen Z., Leng C. Local Linear Estimation of Covariance Matrices via Cholesky Decomposition. Statistica Sinica, 25: 1249–1263, 2015.
[7] Chen Z., Gao Q., Fu B., Zhu H. Monotone Nonparametric Regression for Functional/Longitudinal Data. Statistica Sinica, 29: 2229–2249, 2020.
[8] Chen Z., et al. Efficient Semiparametric Mean-association Estimation for Longitudinal Binary Responses. Statistics in Medicine, 31(13): 1323–1341, 2012.
[9] Chen Z., Tang M.-L., Gao W., Shi N.-Z. New Robust Variable Selection Methods for Linear Regression Models.
Scandinavian Journal of Statistics, 41(3): 725–741, 2014.
[10] Yan F., Xu Q., Tang M.-L., Chen Z.*. Kernel Density-based Likelihood Ratio Tests for Linear Regression
Models. Statistics in Medicine, 40: 119–132, 2021.
[11] Zhu Y., Chen Z., Lawless J. F. Semiparametric Analysis of Interval-censored Failure Time Data with Outcome-
dependent Observation Schemes. Scandinavian Journal of Statistics, 49: 236–264, 2022.
[12] Chen Z., Hu J., Zhu H. Surface Functional Models. Journal of Multivariate Analysis, 180: 104664, 2020.
机器学习与人工智能：
[1] Li S., Chen Z.*, Zhu H., Wang D., Wen W. Nearest-Neighbor Sampling Based Conditional Independence Testing.
AAAI 2023, 37(7): 8631–8639. (Oral, CCF-A)
[2] Li S., Zhang Y., Zhu H., Wang D., Shu H., Chen Z.*, et al. K-Nearest-Neighbor Local Sampling Based
Conditional Independence Testing. NeurIPS 2023, 36: 23321–23344. (CCF-A)
[3] Yang Y., Li S., Zhang Y., Sun Z., Shu H., Chen Z.*. Conditional Diffusion Models Based Conditional
Independence Testing. AAAI 2025, 39(21): 22020–22028. (CCF-A)
[4] Zhang Z., Chen Z.*, Liu Q., Xie J., Zhu H*. Sampling-guided Heterogeneous Graph Neural Network with Temporal
Smoothing for Scalable Longitudinal Data Imputation. ACM SIGKDD 2025: 3912–3920. (CCF-A)
[5] Yang Y., Chen S., Hu P., Shen Z., Zhang Y., Sun Z., Li S., Chen Z.*, Fukumizu K. Conditionally Whitened
Generative Models for Probabilistic Time Series Forecasting. ICLR 2026. (CCF-A)
[6] Zhang Z., Zhu H., Zhang Y., Shu H., Chen Z.*. Enhancing Missing Data Imputation through Combined Bipartite
Graph and Complete Directed Graph. Neurocomputing, 649: 130717, 2025. (中科院 Top)
[7] Shu H., Shi R., Jia Q., Zhu H., Chen Z.*. mFI-PSO: A Flexible and Effective Method in Adversarial Image
Generation for Deep Neural Networks. IJCNN 2022. (Oral)
[8] Wu R., Chen Z., Zhong L., et al. Unleashing Diffusion and State Space Models for Medical Image Segmentation. Journal of Imaging Informatics in Medicine, 2026.
[9] Dang Y., Chen Z., Li H., Shu H.A Comparative Study of Non-deep / Deep / Ensemble Learning Methods for Sunspot Number Prediction. Applied Artificial Intelligence, 36: 2074129, 2022.
