Dapeng Shi

Postdoctoral Fellow
Department of Statistics and Data Science
The Chinese University of Hong Kong

I work with Prof. Junhui Wang at The Chinese University of Hong Kong. I received my Ph.D. in Statistics from the Shanghai Center for Mathematical Sciences, Fudan University, advised by Prof. Zhiliang Ying.

My research interests include statistical network analysis, graphical models, generative models, causal inference, and statistical genetics. My current work focuses on community detection, multilayer networks, and transfer learning for network data.

Academic Experience

Jul. 2025 - present, Postdoctoral Fellow, Department of Statistics and Data Science, The Chinese University of Hong Kong. Mentor: Prof. Junhui Wang.
Sep. 2024 - Jun. 2025, Research Assistant, Department of Statistics and Data Science, The Chinese University of Hong Kong.
Jun. 2024 - Aug. 2024, Visiting Scholar, Department of Statistics and Data Science, Southern University of Science and Technology.

Educational Background

Sep. 2020 - Jun. 2025, Ph.D. in Statistics, Shanghai Center for Mathematical Sciences, Fudan University. Advisor: Prof. Zhiliang Ying.
Sep. 2016 - Jun. 2020, B.S. in Mathematics, School of Mathematical Sciences and Statistics, Lanzhou University.

Publications

Preprints and Manuscripts

Transfer learning for ultra-sparse networks via conditional diffusion models D. Shi, Y. Wang, C. Liu, and J. Wang. Under review.
A multilayer probit network model for community detection with dependent edges and layers D. Shi, H. Zhang, T. Wang, and J. Wang. Journal of the American Statistical Association, in minor revision. 2026.
Influence Maximization via Information Cascade Embedding Y. Wang, D. Shi, and J. Wang. IEEE Transactions on Information Theory, revise and resubmit.

Peer-Reviewed Publications

Simultaneous identification of sparse structures and communities in heterogeneous graphical models D. Shi, T. Wang, and Z. Ying. Journal of Machine Learning Research, 27(148):1-63, 2026. arXiv
MACFIV: A novel framework for nonlinear causal inference in the body mass index-hypertension relationship with many weak and pleiotropic genetic instruments D. Chen, Y. Wang, D. Shi, Y. Cao, and Y.-Q. Hu. Briefings in Bioinformatics, 27(1):bbaf714, 2026.
A flexible semiparametric approach for robust causal inference with invalid instruments and unmeasured confounder Y. Cao, Y. Wang, D. Shi, D. Chen, and Y.-Q. Hu. Statistical Methods in Medical Research, 35(6):1230-1242, 2026.
Global evidence that plant diversity suppresses pests and promotes plant performance and crop production N.-F. Wan, Y. Wang, L. Fu, …, D. Shi, …, C. Scherber. Nature Ecology & Evolution, 10(2):293-307, 2026.
Understanding biodiversity effects on trophic interactions with a robust approach to path analysis Y. Wang, D. Shi, C. Scherber, …, N.-F. Wan. Cell Reports Sustainability, 2(5):100362, 2025.
Instrumental variable model average with applications in nonlinear causal inference D. Chen, Y. Wang, D. Shi, Y. Cao, and Y.-Q. Hu. Statistics in Medicine, 43(30):5814-5836, 2024.
MR-BOIL: Causal inference in one-sample Mendelian randomization for binary outcome with integrated likelihood method D. Shi, Y. Wang, Z. Zhang, Y. Cao, and Y.-Q. Hu. Genetic Epidemiology, 47(4):332-357, 2023.

Research Talks

11/2025, Talk at Shanghai Center for Mathematical Sciences, Fudan University.
5/2025, Talk at National University of Singapore, Frontiers of Statistical Network Analysis.

Teaching

Mathematical Statistics, Spring 2022, Fudan University. Teaching Assistant.
Advanced Mathematics, Fall 2020 and Spring 2021, Fudan University. Teaching Assistant.