Shaowen Wang

King Abdullah University of Science and Technology

Thuwal, Saudi Arabia

shaowen.wang@kaust.edu.sa

I am a postdoctoral fellow at the King Abdullah University of Science and Technology (KAUST), working on computational seismology and machine learning for the wave equation.

My research develops differentiable wave-physics solvers and implicit neural representations (INRs) for full-waveform inversion (FWI) and seismic imaging. I am the author of SWEEP, a unified framework for differentiable wave simulation, and I work on multiresolution hash-encoded implicit FWI and neural reparameterization.

I am also interested in deep learning for seismic data processing — denoising, deblending, and the attenuation of multiples and shear-wave leakage in ocean-bottom-node (OBN) data — as well as efficient forward modeling, absorbing boundaries, GPU acceleration, and high-performance computing (HPC) for large-scale seismic problems.

Feel free to reach out by email, or find my code on GitHub and my papers on Google Scholar.

news

Oct 01, 2026	Preprint Coarse-to-fine multi-resolution hash encoding for implicit full waveform inversion is on arXiv: hash-encoding levels are switched on from coarse to fine, so the long-wavelength background is resolved before high-wavenumber detail.
Aug 19, 2026	Gave three oral talks at IMAGE 2026 in Houston, all built on hash-encoded neural representations: seismic data interpolation, DAS data compression, and implicit FWI with diffusion-model regularization.
Jul 11, 2026	Our paper Implicit full waveform inversion imaging is published in Geophysical Journal International.
Jun 08, 2026	Four abstracts at the 87th EAGE Annual Conference & Exhibition in Aberdeen, UK — see publications.
Apr 01, 2026	The SWEEP preprint is on arXiv; documentation at sweepx.deepwave.group.

selected publications

Implicit Full Waveform Inversion Imaging

Shaowen Wang and Tariq Alkhalifah

Geophysical Journal International, 2026

DOI Bib

@article{wang2026ifwiimaging,
  title = {{Implicit Full Waveform Inversion Imaging}},
  author = {Wang, Shaowen and Alkhalifah, Tariq},
  journal = {Geophysical Journal International},
  year = {2026},
  doi = {10.1093/gji/ggag277}
}

SWEEP (Seismic Wave Equation Exploration Platform): A Unified Solver Framework for Differentiable Wave Physics

Shaowen Wang and Tariq Alkhalifah

arXiv preprint, 2026

arXiv Bib

@article{wang2026sweep,
  title = {{SWEEP (Seismic Wave Equation Exploration Platform): A Unified Solver Framework for Differentiable Wave Physics}},
  author = {Wang, Shaowen and Alkhalifah, Tariq},
  journal = {arXiv preprint},
  year = {2026},
}

Multiresolution Hash Encoding for High Resolution Implicit Full Waveform Inversion

Shaowen Wang, Matteo Ravasi, and Tariq Alkhalifah

In 86th EAGE Annual Conference & Exhibition, 2025

DOI Bib

@inproceedings{wang2025mrhash,
  title = {{Multiresolution Hash Encoding for High Resolution Implicit Full Waveform Inversion}},
  author = {Wang, Shaowen and Ravasi, Matteo and Alkhalifah, Tariq},
  booktitle = {86th EAGE Annual Conference & Exhibition},
  year = {2025},
  doi = {10.3997/2214-4609.202510109}
}

Memory Optimization in RNN-based Full Waveform Inversion using Boundary Saving Wavefield Reconstruction

Shaowen Wang, Y. Jiang, P. Song, and 3 more authors

IEEE Transactions on Geoscience and Remote Sensing, 2023

DOI Bib

@article{wang2023memory,
  title = {{Memory Optimization in RNN-based Full Waveform Inversion using Boundary Saving Wavefield Reconstruction}},
  author = {Wang, Shaowen and Jiang, Y. and Song, P. and Tan, J. and Liu, Z. and He, B.},
  journal = {IEEE Transactions on Geoscience and Remote Sensing},
  year = {2023},
  doi = {10.1109/TGRS.2023.3317529}
}

Deep Learning-based Attenuation for Shear-wave Leakage from Ocean-bottom Node Data

Shaowen Wang, P. Song, J. Tan, and 4 more authors

Geophysics, 2023

DOI Bib

@article{wang2023shearwave,
  title = {{Deep Learning-based Attenuation for Shear-wave Leakage from Ocean-bottom Node Data}},
  author = {Wang, Shaowen and Song, P. and Tan, J. and He, B. and Xia, D. and Wang, Q. and Du, G.},
  journal = {Geophysics},
  year = {2023},
  doi = {10.1190/geo2022-0252.1}
}

Attention-based Neural Network for Erratic Noise Attenuation from Seismic Data with a Shuffled Noise Training Data Generation Strategy

Shaowen Wang, P. Song, J. Tan, and 3 more authors

IEEE Transactions on Geoscience and Remote Sensing, 2022

DOI Bib

@article{wang2022attention,
  title = {{Attention-based Neural Network for Erratic Noise Attenuation from Seismic Data with a Shuffled Noise Training Data Generation Strategy}},
  author = {Wang, Shaowen and Song, P. and Tan, J. and He, B. and Wang, Q. and Du, G.},
  journal = {IEEE Transactions on Geoscience and Remote Sensing},
  year = {2022},
  doi = {10.1109/TGRS.2022.3197929}
}