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Publications

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2026

  • Jie, Y., Wei, S. S., Zhu, W., Freymueller, J., Elliott, J. (2026). Deep-Learning-Based Catalog of Background Seismicity and Aftershocks of the 2020–2021 Large Earthquakes Along the Alaska Peninsula. Seismological Research Letters. doi · pdf
  • Wolf, J., Romanowicz, B., Garnero, E., Zhu, W., West, J. D. (2026). Widespread Deformation at the Base of the Mantle Linked to Subducted Slabs. The Seismic Record. doi · pdf
  • Zhang, C., Zhu, W., Romanowicz, B. A., Allen, R. M., Soga, K., Wu, Y. (2026). A Deep Learning Framework for Marine Acoustic and Seismic Monitoring with Distributed Acoustic Sensing. arXiv preprint. doi · pdf
  • Zhu, C., Yang, Y., Yang, K., Zhu, W., Yang, Q. (2026). Monitoring Landslide Disturbances Using Distributed Acoustic Sensing under Extreme Weather Conditions. npj Natural Hazards. doi · pdf

2025

  • Ding, Q., Shen, Z., Zhu, W., Liu, B. (2025). DASFormer: Self-Supervised Pretraining for Earthquake Monitoring. Visual Intelligence. doi · pdf
  • Gou, Y., Allen, R. M., Zhu, W., Taira, T., Chen, L. (2025). Leveraging Submarine DAS Arrays for Offshore Earthquake Early Warning: A Case Study in Monterey Bay, California. Bulletin of the Seismological Society of America. doi · pdf
  • Poggiali, G., Chiaraluce, L., Ross, Z. E., Zhu, W., Marone, C. (2025). Fault Geometry and Source Mechanics of the Altotiberina Fault System from a High-Resolution Machine-Learning Earthquake Catalog. Bulletin of the Seismological Society of America. doi · pdf
  • Song, J., Zhu, W., Zi, J., Yang, H., Chu, R. (2025). An Enhanced Focal Mechanism Catalog of Induced Earthquakes in Weiyuan, Sichuan, from Dense Array Data and a Multitask Deep Learning Model. The Seismic Record. doi · pdf
  • Suzuki, R., Uchida, N., Zhu, W., Beroza, G. C., Nakayama, T., Yoshida, K., Toyokuni, G., Takagi, R., Azuma, R., Hasegawa, A. (2025). The Forearc Seismic Belt: A Fluid Pathway Constraining Down-Dip Megathrust Earthquake Rupture. Science. doi · pdf
  • Tepp, G., Yu, E., Bhaskaran, A., Tam, R., Zhu, W., Newman, Z., Jaski, E., Scheckel, N. (2025). Improvements from Incorporating Machine Learning Algorithms into Near Real-Time Operational Post-Processing. Scientific Reports. doi · pdf
  • Zhu, W., Rong, B., Jie, Y., Wei, S. S. (2025). Robust Earthquake Location Using Random Sample Consensus (RANSAC). arXiv preprint. doi · pdf
  • Zhu, W., Song, J., Wang, H., Münchmeyer, J. (2025). Towards End-to-End Earthquake Monitoring Using a Multitask Deep Learning Model. arXiv preprint. doi · pdf
  • Zhu, W., Wang, H., Rong, B., Yu, E., Zuzlewski, S., Tepp, G., Taira, T., Marty, J., Husker, A., Allen, R. M. (2025). California Earthquake Dataset for Machine Learning and Cloud Computing. arXiv preprint. doi · pdf

2024

  • Atterholt, J., Zhan, Z., Yang, Y., Zhu, W. (2024). Imaging the Garlock Fault Zone with a Fiber: A Limited Damage Zone and Hidden Bimaterial Contrast. Journal of Geophysical Research: Solid Earth. doi · pdf
  • Feng, Y., Zhu, W., Lu, X. (2024). QuakeFormer: A Uniform Approach to Earthquake Ground Motion Prediction Using Masked Transformers. arXiv preprint. doi · pdf
  • Xi, Z., Wei, S. S., Zhu, W., Beroza, G. C., Jie, Y., Saloor, N. (2024). Deep Learning for Deep Earthquakes: Insights from OBS Observations of the Tonga Subduction Zone. Geophysical Journal International. doi · pdf

2023

  • Biondi, E., Zhu, W., Li, J., Williams, E. F., Zhan, Z. (2023). An Upper-Crust Lid over the Long Valley Magma Chamber. Science Advances. doi · pdf
  • Li, J., Zhu, W., Biondi, E., Zhan, Z. (2023). Earthquake Focal Mechanisms with Distributed Acoustic Sensing. Nature Communications. doi · pdf
  • Ross, Z. E., Zhu, W., Azizzadenesheli, K. (2023). Neural Mixture Model Association of Seismic Phases. arXiv preprint. doi · pdf
  • Sun, H., Ross, Z. E., Zhu, W., Azizzadenesheli, K. (2023). Phase Neural Operator for Multi-Station Picking of Seismic Arrivals. Geophysical Research Letters. doi · pdf
  • Wilding, J. D., Zhu, W., Ross, Z. E., Jackson, J. M. (2023). The Magmatic Web beneath Hawaiʻi. Science. doi · pdf
  • Yin, J., Soto, M. A., Ramírez, J., Kamalov, V., Zhu, W., Husker, A., Zhan, Z. (2023). Real-Data Testing of Distributed Acoustic Sensing for Offshore Earthquake Early Warning. The Seismic Record. doi · pdf
  • Yin, J., Zhu, W., Li, J., Biondi, E., Miao, Y., Spica, Z. J., Viens, L., Shinohara, M., Ide, S., Mochizuki, K., Husker, A., Zhan, Z. (2023). Earthquake Magnitude with DAS: A Transferable Data-Based Scaling Relation. Geophysical Research Letters. doi · pdf
  • Zhu, W., Biondi, E., Li, J., Yin, J., Ross, Z. E., Zhan, Z. (2023). Seismic Arrival-Time Picking on Distributed Acoustic Sensing Data Using Semi-Supervised Learning. Nature Communications. doi · pdf

2022

  • Datta, A., Wu, D. J., Zhu, W., Cai, M., Ellsworth, W. L. (2022). DeepShake: Shaking Intensity Prediction Using Deep Spatiotemporal RNNs for Earthquake Early Warning. Seismological Research Letters. doi · pdf
  • Retailleau, L., Saurel, J., Laporte, M., Lavayssière, A., Ferrazzini, V., Zhu, W., Beroza, G. C., Satriano, C., Komorowski, J. (2022). Automatic Detection for a Comprehensive View of Mayotte Seismicity. Comptes Rendus Géoscience. doi · pdf
  • Retailleau, L., Saurel, J., Zhu, W., Satriano, C., Beroza, G. C., Issartel, S., Boissier, P. (2022). A Wrapper to Use a Machine-Learning-Based Algorithm for Earthquake Monitoring. Seismological Research Letters. doi · pdf
  • Wang, K., Ellsworth, W., Beroza, G. C., Zhu, W., Rubinstein, J. L. (2022). DevelNet: Earthquake Detection on Develocorder Films with Deep Learning: Application to the Rangely Earthquake Control Experiment. Seismological Research Letters. doi · pdf
  • Xu, K., Zhu, W., Darve, E. (2022). Learning Generative Neural Networks with Physics Knowledge. Research in the Mathematical Sciences. doi · pdf
  • Yang, L., Liu, X., Zhu, W., Zhao, L., Beroza, G. C. (2022). Toward Improved Urban Earthquake Monitoring through Deep-Learning-Based Noise Suppression. Science Advances. doi · pdf
  • Zhang, M., Liu, M., Feng, T., Wang, R., Zhu, W. (2022). LOC-FLOW: An End-to-End Machine Learning-Based High-Precision Earthquake Location Workflow. Seismological Research Letters. doi · pdf
  • Zhu, W., Hou, A. B., Yang, R., Datta, A., Mousavi, S. M., Ellsworth, W. L., Beroza, G. C. (2022). QuakeFlow: A Scalable Machine-Learning-Based Earthquake Monitoring Workflow with Cloud Computing. Geophysical Journal International. doi · pdf
  • Zhu, W., McBrearty, I. W., Mousavi, S. M., Ellsworth, W. L., Beroza, G. C. (2022). Earthquake Phase Association Using a Bayesian Gaussian Mixture Model. Journal of Geophysical Research: Solid Earth. doi · pdf
  • Zhu, W., Tai, K. S., Mousavi, S. M., Bailis, P., Beroza, G. C. (2022). An End-to-End Earthquake Detection Method for Joint Phase Picking and Association Using Deep Learning. Journal of Geophysical Research: Solid Earth. doi · pdf
  • Zhu, W., Xu, K., Darve, E., Biondi, B., Beroza, G. C. (2022). Integrating Deep Neural Networks with Full-Waveform Inversion: Reparameterization, Regularization, and Uncertainty Quantification. Geophysics. doi · pdf

2021

  • Ma, B., Zhu, W., Huang, Q. (2021). Imaging Shallow Fault Structures by Three-Dimensional Reverse Time Migration of Ground Penetration Radar Data. Journal of Applied Geophysics. doi · pdf
  • Tan, Y. J., Waldhauser, F., Ellsworth, W. L., Zhang, M., Zhu, W., Michele, M., Chiaraluce, L., Beroza, G. C., Segou, M. (2021). Machine-Learning-Based High-Resolution Earthquake Catalog Reveals How Complex Fault Structures Were Activated during the 2016–2017 Central Italy Sequence. The Seismic Record. doi · pdf
  • Zhu, W. (2021). Applications of Deep Learning in Seismology. Ph.D. Thesis, Stanford University. pdf
  • Zhu, W., Xu, K., Darve, E., Beroza, G. C. (2021). A General Approach to Seismic Inversion with Automatic Differentiation. Computers & Geosciences. doi · pdf

2020

  • Chai, C., Maceira, M., Santos-Villalobos, H. J., Venkatakrishnan, S. V., Schoenball, M., Zhu, W., Beroza, G. C., Thurber, C. (2020). Using a Deep Neural Network and Transfer Learning to Bridge Scales for Seismic Phase Picking. Geophysical Research Letters. doi · pdf
  • Liu, M., Zhang, M., Zhu, W., Ellsworth, W. L., Li, H. (2020). Rapid Characterization of the July 2019 Ridgecrest, California, Earthquake Sequence from Raw Seismic Data Using Machine-Learning Phase Picker. Geophysical Research Letters. doi · pdf
  • Mousavi, S. M., Ellsworth, W. L., Zhu, W., Chuang, L. Y., Beroza, G. C. (2020). Earthquake Transformer—an Attentive Deep-Learning Model for Simultaneous Earthquake Detection and Phase Picking. Nature Communications. doi · pdf
  • Park, Y., Mousavi, S. M., Zhu, W., Ellsworth, W. L., Beroza, G. C. (2020). Machine-Learning-Based Analysis of the Guy-Greenbrier, Arkansas Earthquakes: A Tale of Two Sequences. Geophysical Research Letters. doi · pdf
  • Xu, K., Zhu, W., Darve, E. (2020). Distributed Machine Learning for Computational Engineering Using MPI. arXiv preprint. doi · pdf
  • Zheng, J., Shen, S., Jiang, T., Zhu, W. (2020). Deep Neural Networks Design and Analysis for Automatic Phase Pickers from Three-Component Microseismic Recordings. Geophysical Journal International. doi · pdf
  • Zhu, W., Allison, K. L., Dunham, E. M., Yang, Y. (2020). Fault Valving and Pore Pressure Evolution in Simulations of Earthquake Sequences and Aseismic Slip. Nature Communications. doi · pdf
  • Zhu, W., Huang, Q., Liu, L., Ma, B. (2020). Three-Dimensional Reverse Time Migration of Ground-Penetrating Radar Signals. Pure and Applied Geophysics. doi · pdf
  • Zhu, W., Mousavi, S. M., Beroza, G. C. (2020). Seismic Signal Augmentation to Improve Generalization of Deep Neural Networks. Advances in Geophysics. doi · pdf

2019

  • Mousavi, S. M., Sheng, Y., Zhu, W., Beroza, G. C. (2019). STanford EArthquake Dataset (STEAD): A Global Data Set of Seismic Signals for AI. IEEE Access. doi · pdf
  • Mousavi, S. M., Zhu, W., Ellsworth, W., Beroza, G. (2019). Unsupervised Clustering of Seismic Signals Using Deep Convolutional Autoencoders. IEEE Geoscience and Remote Sensing Letters. doi · pdf
  • Mousavi, S. M., Zhu, W., Sheng, Y., Beroza, G. C. (2019). CRED: A Deep Residual Network of Convolutional and Recurrent Units for Earthquake Signal Detection. Scientific Reports. doi · pdf
  • Zhu, W., Mousavi, S. M., Beroza, G. C. (2019). Seismic Signal Denoising and Decomposition Using Deep Neural Networks. IEEE Transactions on Geoscience and Remote Sensing. doi · pdf

2018

  • Zhu, W., Beroza, G. C. (2018). PhaseNet: A Deep-Neural-Network-Based Seismic Arrival-Time Picking Method. Geophysical Journal International. doi · pdf

2016

  • Zhu, W., Huang, Q. (2016). Attenuation Compensated Reverse Time Migration Method of Ground Penetrating Radar Signals. Chinese Journal of Geophysics.