2020-2024, Ph.D.

GitHub: sixu0

Google Scholar: Xu Si

Email: xusi@mail.ustc.edu.cn

Master: Geophysics, CUG (Beijing), 2017-2020.

Undergraduate: Geophysics, CUG (Wuhan), 2013-2017.

Personal page: https://sixu0.github.io/

Research: graph neural network, deep learning, seismology, seismic location

Experience: Summer Intern, Anhui Earthquake Agency, 2020; Cloud Computing Engineer, Summer Intern, Huawei, 2021.

Publication

11. Si, X., X. Wu*, H. Sheng, J. Zhu, and Z. Li, 2023, SeisCLIP: A seismology foundation model pre-trained by multi-modal data for multi-purpose seismic feature extraction, submitted. [Code], [Arxiv].

10. Si, X., X. Wu*, Z. Li*, S. Wang, and J. Zhu, 2023, Multi-task multi-station earthquake monitoring: An all-in-one seismic Phase picking, Location, and Association Network (PLAN), submitted. [Arxiv].

9. Wu, X., J. Ma, X. Si, Z. Bi, J. Yang, H. Gao, D. Xie, Z. Guo, and J. Zhang, 2023, Sensing prior constraints in deep neural networks for solving geophysical problems, PNAS, Vol. 120(23), e2219573120.

8. Wang, S., Z. Cai*, X. Si, and Y. Cui, 2023, A Three-Dimensional Geological Structure Modeling Framework and Its Application in Machine Learning, Math Geosci, 55, 163–200 (2023).

7. Wang, S., X. Si*, Z. Cai, and Y. Cui, 2023, Structural Augmentation in Seismic Data for Fault Prediction, Appl. Sci, 2022, 12(19), 9796.

6. Jiang, L., X. Si, and X. Wu*, 2022, Filling borehole image gaps with partial convolution neural network. Geophysics, submitted. [FIG].

5. Zhang, Q., W. Zhang*, X. Wu*, J. Zhang, W. Kuang, and X. Si, 2022, Deep Learning for efficient microseismic location using source migration-based imaging, JGR, Solid Earth, Vol. 127(3), 1-19. [PDF], [FIG].

4. Yuan, X. Si, and Y. Zheng, 2020, Ground roll attenuation using generative adversarial network. Geophysics, 85(4), 1JA-Z18.

3. Si, X., Y. Yuan, T. Si, and S. Gao, 2019, Attenuation of random noise using denoising convolutional neural networks. Interpretation, 7(3): SE269-SE280.

2. Si, X., Y. Yuan, F. Ping, Y. Zheng, and L. Feng, 2019, Ground roll attenuation based on conditional and cycle generative adversarial networks. SEG Workshop on Mathematical Geophysics: Traditional vs Learning. (Best student poster)

1. Li. F., X. Si, F. Li, and J. Gao, 2019, 2-D Seismic Data Reconstruction with Conditional Generative Adversarial Networks. SEG Workshop on Mathematical Geophysics: Traditional vs Learning.

Miniposter

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