Yi Ding holds a Ph.D. in Engineering. His research focuses on forward and inverse modeling of wave propagation, strong ground motion simulation, and intelligent simulation methods for blasting. He leads one Young Scientists Fund project funded by the National Natural Science Foundation of China (NSFC) and has contributed to subprojects under the NSFC Major Program and projects under the National Key R&D Program of China. He has published more than 20 SCI/EI-indexed papers, including eight as first or corresponding author and three in journals designated as Q1 Top journals by the Chinese Academy of Sciences. He holds three granted invention patents.
Contact:dingyi18@mails.ucas.edu.cn
Education and Professional Experience:
September 2025–present: State Key Laboratory of Precision Blasting, Jianghan University
October 2023–October 2024: Joint Doctoral Training, The University of Tokyo
September 2021–June 2025: Ph.D. in Engineering, Civil Engineering, Beijing University of Technology
September 2018–June 2021: M.Eng. in Disaster Prevention and Mitigation Engineering and Protective Engineering, Institute of Geophysics, China Earthquake Administration
September 2014–June 2018: B.Eng. in Urban Underground Space Engineering, Nanjing Tech University
Selected Research Projects:
1.NSFC Young Scientists Fund (Category C): Consistent Broadband Ground Motion Simulation Integrating Low-Frequency Physics Constraints with High-Frequency Generative Modeling. January 2027–December 2029; Principal Investigator.
2.Doctoral Research Start-up Fund, Hubei (Wuhan) Institute of Explosion and Blasting Technology: Mechanisms Governing the Initiation of Propagating Ruptures on Prestressed Faults under Blasting-Induced Disturbances. September 2026–September 2029; funding: Principal Investigator.
3.National Key R&D Program of China: Key Technologies for Large-Earthquake Hazard Analysis for Major Infrastructure Crossing Active Faults. Core Research Team Member.
4.Subproject under the NSFC Major Program: Characterization and Simulation of the Spatiotemporally Coupled Effects of Great Earthquakes and Giant Landslides on Cascaded Hydropower Complexes. Core Research Team Member.
1.Yi Ding, Su Chen, Hujin Jun, et al. Wavelet Packet-Based Diffusion Model for Ground Motion Generation with Multi-Conditional Energy and Spectral Matching. Computer-Aided Civil and Infrastructure Engineering, 2026. (IF=9.2)
2.Yi Ding, Su Chen, Hujin Jun, et al. Wavelet Packet-Based Diffusion Model for Ground Motion Generation with Multi-Conditional Energy and Spectral Matching. Earthquake Engineering & Structural Dynamics, 2026. (IF=5.0)
3.Yi Ding, Su Chen, Hiroe Miyake, et al. Physics-informed Neural Networks with Fourier Features for Seismic Wavefield Simulation in Time-Domain Nonsmooth Complex Media. IEEE Transactions on Geoscience and Remote Sensing, 2025, 63: 1-13. (IF=9.4)
4.Yi Ding, Su Chen, Xiaojun Li, et al. Self-adaptive physics-driven deep learning for seismic wave modeling in complex topography. Engineering Applications of Artificial Intelligence, 2023, 123, 106425. (IF=9.0)
5.Yi Ding, Su Chen, Xiaojun Li, et al. Physics-constrained neural networks for half-space seismic wave modeling. Computers & Geosciences, 2023, 181, 105477. (IF=4.2)
6.Chen S., Ding Y*., Miyake H., Li X., Discovery and inversion of the viscoelastic wave equation in inhomogeneous media. Computer Physics Communications, 2025, 312: 109599. (F=7.2)
7.Xiaohu Hu, Su Chen, Yi Ding, Lei Fu, Xiaojun Li, Spectrum-compatible artificial accelerograms via conditional variational autoencoder with generative adversarial networks. Engineering Structures, 348: 121766. (IF=7.6)
8.Qingxu Zhao, Mianshui Rong, Yi Ding, et al. Unsupervised characterization of site conditions from detailed information for improved ground motion modeling. Engineering Geology, 2026, 360: 108489. (IF=10.3)
9.Yi Ding, Jinjun Hu, Su Chen, et al. 2026. A multi-condition constrained diffusion method for ground motion generation with energy and response spectrum matching. China Civil Engineering Journal. (In Chinese)
10.Su Chen, Yi Ding, Hao Sun, et al. 2023. Physics-driven deep learning for numerical simulation of wave propagation and its applications. Chinese Journal of Theoretical and Applied Mechanics, 55, 272–282. (In Chinese)
11.Yi Ding, Yushi Wang, Wang Ning, et al. Nonlinear statistical characteristics and influencing factors of surface-to-borehole response spectral ratios. Technology for Earthquake Disaster Prevention,2021,16(02):362-370. (In Chinese)
