X. Zhang, S. Jiang*, N. Zheng, X. Xia, Z. Li, R. Zhang, and X. Wang, Integration of DDPM and ILUES for Simultaneous Identification of Contaminant Source Parameters and Non-Gaussian Channelized Hydraulic Conductivity Field, Water Resources Research, 2024, https://doi.org/10.1029/2023WR036893.

X. Zhang, S. Jiang*, J. Wei, Chao Wu, X. Wang, X. Xia, N. Zheng, J. Xing, Non-Gaussian Hydraulic Conductivity and Potential Contaminant Source Identification: A Comparison of Two Advanced DLPM-based Inversion Framework, Journal of Hydrology, 2024, https://doi.org/10.1016/j.jhydrol.2024.131540.

M. Guo, N. Zhou*, Y. Cai, X. Wang, X. Zhang, S. Lu, K. Liu, W. Zhao, Quantitative estimation of vegetation carbon source/sink and its response to climate variability and anthropogenic activities in Dongting Lake Wetland, China, Remote Sensing, 2025, https://doi.org/10.3390/rs17142475.

J. Wei, S. Jiang*, Q. Liu, X. Zhang, Toward Closed-Loop Remediation: A Dynamic Optimization Approach for Hydraulic Conductivity Estimation and Pump-and-Treat Design, Accepted by Journal of Contaminant Hydrology, 2025.

X. Zhang, W. Yang, J. Zhang, S. Jiang*, Diffusion-Inversion-Net (DIN): An End-to-End Direct Probabilistic Framework for Characterizing Hydraulic Conductivities and Quantifying Uncertainty, Geophysical Research Letters, Under Review, 2025, https://arxiv.org/abs/2511.16926.

W. Yang, X. Zhang*, S. Jiang, PIS: A Generalized Physical Inversion Solver for Arbitrary Sparse Observations via Set-Conditioned Diffusion, In preparation for ICML 2026, https://doi.org/10.13140/RG.2.2.23577.68963.

W. Yang, X. Zhang*, S. Jiang, Parameter Estimation of Groundwater PDEs Across Varied Scenarios: A Comparative Evaluation of Diffusion Models and Flow Matching, In preparation for KDD 2026.

B. Zhang, F. Wang*, X. Zhang, From flood to debris flood: Initial and cascading destabilization of sediment as critical mechanisms, Submitted to Journal of Hydrology, 2025.

The 9th Young Scholars' Forum in Groundwater Science (Nov. 2025): X. Zhang (presenter), S. Jiang*, Prospects of Deep Generative Models in Groundwater Parameter Inversion: From Parameterization to Direct Inversion Modeling. Oral presentation, Session 3, Hefei, China.

The 35th KKHTCNN Symposium on Civil Engineering (Nov. 2024): X. Zhang (presenter), S. Jiang*, Non-gaussian hydraulic conductivity and potential contaminant source identification: A comparison of two advanced DLPM-based inversion framework. Oral presentation, Track 5, Shanghai, China.

International Forum on Groundwater (Aug. 2024): X. Zhang (presenter), S. Jiang*, Leveraging Deep Generative Models for Enhanced Hydraulic Conductivity Estimation in Groundwater Modeling. Oral presentation, Session 14, Jilin, China. Outstanding Graduate Student Presentation Award