Yang Senlin (杨森林)

PhD Students

Visiting Student

Visiting

Biography

Senlin Yang received the B.S degree in engineering from Shandong University, China (2017). Since 2017, he has been pursuing his PhD degree in Shandong University. Currently, he is a visiting PhD student in SWAG, KAUST.  His research interests include deep-learning based geophysical data processing and inversion, and the tunnel geological forward-prospecting.

Research Interest

Deep learning-based seismic velocity inversion, tunnel geological forward-prospecting, and other applications of deep learning in geophysical data.

Selected Publications

[1] Senlin Yang, Zhengfang Wang, Jing Wang*, Anthony G. Cohn, Jiaqi Zhang, Peng Jiang, Qingmei Sui. Defect segmentation: Mapping tunnel lining internal defects with ground penetrating radar data using a convolutional neural network. Construction and Building Materials, 2022, Volume: 319, Page: 125658.  DOI: 10.1016/j.conbuildmat.2021.125658.

[2] Bin Liu, Senlin Yang, Yuxiao Ren, Xinji Xu, Yangkang Chen, Peng Jiang*. Deep learning seismic full waveform inversion for realistic structural models. Geophysics, 2021, Volume: 86, Issue: 1, Page: R31-R44. DOI: 10.1190/geo2019-0435.1. 

[3] Xu Guo, Jiansen Wang, Senlin Yang, Yuxiao Ren*. Optimal staggered-grid finite-difference method for wave modeling based on artificial neural networks. Computers & Mathematics with Applications, 2022, Volume: 108, Page: 141-158. DOI: 10.1016/j.camwa.2022.01.012. 

[4] Yuxiao Ren, Xinji Xu*, Senlin Yang, Lichao Nie*, Yangkang Chen. A physics-based neural-network way to perform seismic full waveform inversion. IEEE Access, 2020, Volume: 8, Page: 112266-112277. DOI: 10.1109/ACCESS.2020.2997921.  

[5] Shucai Li*, Bin Liu, Yuxiao Ren, Yangkang Chen, Senlin Yang, Yunhai Wang, Peng Jiang. Deep-learning Inversion of Seismic Data. IEEE Transactions on Geoscience and Remote Sensing, 2020, Volume: 58, Issue: 3, Page: 2135-2149. DOI: 10.1109/TGRS.2019.2953473. 

Education

2013 - 2017        BS,  School of Control Science and Engineering, Shandong University, China

2017 - Present   PhD,  School of Qilu Transportation, Shandong University, China

Scientific and Professional Membership

Society of Exploration Geophysicists student member

Chinese Geophysical Society student member

KAUST Affiliations

Seismic Wave Analysis Group (SWAG), Earth Science and Engineering (ErSE) Program

Non-KAUST Affiliations

Geotechnical and Structural Engineering Research Center, Shandong University;

School of Qilu Transportation, Shandong University

Research Interests Keywords

Deep learning Seismic imaging & inversion with deep learning Geophysics