Publications

In Review

[98] *Li, L., & Ross, Z. E. (n.d.). "On the Frequency and Timing of Earthquake Doublets [submitted].

[97] ^Shi, Y., Ross, Z. E., & Yue, Y. (n.d.). Flow Annealing Posterior Sampling for Function Space Regression and Inverse Problems [submitted].

[96] *Shi, Y., Lavrentiadis, G., Tsalouchidis, K., Ross, Z. E., McCallen, D., Zou, C., Azizzadenesheli, K., & Asimaki, D. (n.d.). Large-Scale 3D Ground-Motion Synthesis with PhysicsInspired Latent Operator Flow Matching [submitted].

[95] Poggiali, G., Chiaraluce, L., Sugan, M., Vuan, A., Ross, Z. E., & Marone, C. (n.d.). Spatiotemporal Evolution of Seismicity in the Northern Apennines: Insights from a High-Resolution Earthquake Catalog [submitted].

[94] *Villa, V., Ross, Z. E., & Lapusta, N. (n.d.). Whispers of aftershocks in the seismically prolific San Jacinto Fault Zone, California [submitted].

[93] ^Guo, H., Wilding, J. D., & Ross, Z. E. (n.d.). Tidal modulation of earthquake rates in tensilely deformed environments [submitted].

[92] ^Ramirez, E. E., Stock, J. M., Ross, Z. E., Vidal-Villegas, J. A., Núñez-Leal, M. A., & Ramírez-Hernández, J. (n.d.). Northern Baja California, Mexico, Seismicity Illuminated with Deep Learning Phase Picking and Associator [submitted].

Published

[91] Ross, Z. E., Wilding, J. D., Azizzadenesheli, K., & Kato, A. (2026). SPIDER: Scalable Probabilistic Inference for Differential Earthquake Relocation. Journal of Geophysical Research: Solid Earth, 131(3), e2025JB032769.

[90] *Wilding, J. D., Wang, T. A., Liu, Y.-K., & Ross, Z. E. (2026). Cascading magmatic unrest and aseismic faulting in the Aegean Sea enabled by elastic stress relay [in press]. Science Advances.

[89] *Kong, C., Gurnis, M., & Ross, Z. E. (2026). Forward and inverse mantle convection with neural operators. Geophysical Journal International, 246(3), ggag255.

[88] *Zou, C., Shi, Y., Ross, Z. E., Clayton, R. W., & Azizzadenesheli, K. (2026). Enforcing Reciprocity in Operator Learning for Seismic Wave Propagation. Seismological Research Letters. https://doi.org/10.1785/0220260082

[87] *Gao, A. F., Wilding, J. D., Biondi, E., Bouman, K. L., & Ross, Z. E. (2026). High-resolution Eikonal imaging and uncertainty quantification of the Kilauea caldera. Geophysical Journal International, ggag179. https://doi.org/10.1093/gji/ggag179

[86] ^Chen, Z., McPhillips, D., Scharer, K., & Ross, Z. E. (2026). 3D Semantic Mapping of surface geological features. Computers & Geosciences, 106181.

[85] ^Ragon, T., Gao, A. F., & Ross, Z. E. (2025). DeepGEM-EGF: A Bayesian strategy for joint estimates of source-time functions and Empirical Green's functions. Journal of Geophysical Research: Solid Earth, 130, e2025JB031260. https://doi.org/10.1029/2025JB031260

[84] *Shi, Y., Ross, Z. E., Asimaki, D., & Azizzadenesheli, K. (2025a). Mesh-Informed Neural Operator: A Transformer Generative Approach. Transactions on Machine Learning Research. https://openreview.net/forum?id=K8qAuRfv0G

[83] *Shi, Y., Ross, Z. E., Asimaki, D., & Azizzadenesheli, K. Stochastic Process Learning via Operator Flow Matching [Spotlight Paper]. In Advances in neural information processing systems (neurips). Spotlight Paper. 2025.

[82] *Zou, C., Ross, Z. E., Clayton, R. W., Lin, F.-C., & Azizzadenesheli, K. (2025). Ambient noise full waveform inversion with neural operators. Journal of Geophysical Research: Solid Earth, 130, e2025JB031624. https://doi.org/10.1029/2025JB031624

[81] Kong, Q., Zou, C., Choi, Y., Matzel, E. M., Azizzadenesheli, K., Ross, Z. E., Rodgers, A. J., & Clayton, R. W. (2025). Reducing Frequency Bias of Fourier Neural Operators In 3D Seismic Wavefield Simulations Through Multi-Stage Training. Seismological Research Letters. https://doi.org/10.1785/0220250085

[80] ^Poggiali, G., Chiaraluce, L., Ross, Z. E., Zhu, W., & Marone, C. (2025). A High Resolution Machine-Learning Earthquake Catalog to Characterize Fault Geometry and Source Mechanics: the Altotiberina Fault Case Study. Bulletin of the Seismological Society of America. https://doi.org/10.1785/0120250072

[79] Zheng, H., Chu, W., Zhang, B., Wu, Z., Wang, A., Feng, B., Zou, C., Sun, Y., Kovachki, N., Ross, Z. E., Bouman, K., & Yue, Y. InverseBench: Benchmarking Plug-and-Play Diffusion Models for Scientific Inverse Problems [Spotlight Paper]. In International conference on learning representations (iclr). Spotlight Paper. 2025.

[78] *Atterholt, J., Wilding, J. D., & Ross, Z. E. (2024). The Evolution of Fault Orientation in the 2019 Ridgecrest Earthquake Sequence with a New Long-Term Catalog of Seismicity and Moment Tensors. Geophysical Journal International.

[77] *Shi, Y., Gao, A. F., Ross, Z. E., & Azizzadenesheli, K. (2024a). Universal Functional Regression with Neural Operator Flows [in press]. Transactions on Machine Learning Research.

[76] *Wilding, J. D., & Ross, Z. E. (2024b). Rift zone architecture and inflation-driven seismicity of Mauna Loa volcano. Journal of Geophysical Research: Solid Earth, 129, e2024JB029726. https://doi.org/10.1029/2024JB029726

[75] *Zou, C., Azizzadenesheli, K., Ross, Z. E., & Clayton, R. W. (2024). Deep Neural Helmholtz Operators for 3D Elastic Wave Propagation and Inversion. Geophysical Journal International. https://doi.org/10.1093/gji/ggae342

[74] Sirorattanakul, K., Wilding, J. D., Acosta, M., Li, Y., Ross, Z. E., Bourne, S. J., van Elk, J., & Avouac, J.-P. (2024). Bursts of fast propagating swarms of induced earthquakes at the Groningen gas field. Seismological Research Letters. https://doi.org/10.1785/0220240107

[73] *Wilding, J. D., & Ross, Z. E. (2024a). Insights on the state of stress in the mantle beneath Pahala, Hawai‘i. Volcanica, 7(1), 1–19. https://doi.org/10.30909/vol.07.01.0119

[72] *Shi, Y., Lavrentiadis, G., Asimaki, D., Ross, Z. E., & Azizzadenesheli, K. (2024b). Broadband Ground Motion Synthesis via Generative Adversarial Neural Operators: Development and Validation. Bulletin of the Seismological Society of America, 114(4), 2151–2171. https: //doi.org/10.1785/0120230207

[71] Ross, Z. E. (2024). Insights on the dip of fault zones in Southern California from modeling of seismicity with anisotropic point processes. Seismica, 3(1). https://doi.org/10.26443/ seismica.v3i1.1092

[70] *Atterholt, J., & Ross, Z. E. (2024). Finite Source Properties of Large Strike-Slip Earthquakes. Geophysical Journal International, 236(2), 889–903. https://doi.org/10.1093/gji/ ggad459

[69] ^Sun, H., Ross, Z. E., Zhu, W., & Azizzadenesheli, K. (2023). Phase Neural Operator for Multi-Station Picking of Seismic Arrivals. Geophysical Research Letters, 50, e2023GL106434. https://doi.org/10.1029/2023GL106434

[68] ^Zhu, W., Biondi, E., Li, J., Yin, J., Ross, Z. E., & Zhan, Z. (2023). Seismic Arrivaltime Picking on Distributed Acoustic Sensing Data using Semi-supervised Learning. Nature Communications, 14(1), 8192. https://doi.org/10.1038/s41467-023-43355-3

[67] Rahman, M. A., Ross, Z. E., & Azizzadenesheli, K. (2023). U-NO: U-shaped Neural Operators. Transactions on Machine Learning Research. https://openreview.net/forum?id= j3oQF9coJd

[66] Cochran, E. S., Page, M., van der Elst, N. J., Ross, Z. E., & Trugman, D. T. (2023). Fault Roughness at Seismogenic Depths and Links to Earthquake Behavior. The Seismic Record, 3(1), 37–47. https://doi.org/10.1785/0320220043

[65] *Yang, Y., Gao, A. F., Azizzadenesheli, K., Clayton, R. W., & Ross, Z. E. (2023). Rapid Seismic Waveform Modeling and Inversion With Neural Operators [Art no. 5906712]. IEEE Transactions on Geoscience and Remote Sensing, 61, 1–12. https://doi.org/10.1109/TGRS. 2023.3264210

[64] *Muir, J. B., & Ross, Z. E. (2023). Aseismic forcing during the 2016-2020 Cahuilla swarm sequence determined with a deep Gaussian process model. Geophysical Journal International, ggad074. https://doi.org/10.1093/gji/ggad074

[63] *Wilding, J. D., Zhu, W., Ross, Z. E., & Jackson, J. M. (2022). The magmatic web beneath Hawai‘i. Science, 379(6631), 462–468. https://doi.org/10.1126/science.ade5755

[62] *Sirorattanakul, K., Ross, Z. E., Khoshmanesh, M., Cochran, E. S., Acosta, M., & Avouac, J.-P. (2022). The 2020 Westmorland, California earthquake swarm as aftershocks of a slow slip event sustained by fluid flow. Journal of Geophysical Research: Solid Earth, 127, e2022JB024693. https://doi.org/10.1029/2022JB024693

[61] Rahman, M. A., Florez, M. A., Anandkumar, A., Ross, Z. E., & Azizzadenesheli, K. (2022). Generative Adversarial Neural Operators. Transactions on Machine Learning Research. https: //openreview.net/forum?id=X1VzbBU6xZ

[60] Ross, Z. E., Ben-Zion, Y., & Zaliapin, I. (2022). Geometrical properties of seismicity in California. Geophysical Journal International, 231(1), 493–504. https://doi.org/10.1093/gji/ ggac189

[59] *Wilding, J. D., & Ross, Z. E. (2022). Aftershock moment tensor scattering. Geophysical Research Letters, 49, e2022GL098473. https://doi.org/10.1029/2022GL098473

[58] *Atterholt, J., & Ross, Z. E. (2022). Bayesian framework for inversion of second-order stress glut moments: application to the 2019 Ridgecrest Sequence Mainshock. Journal of Geophysical Research: Solid Earth, e2021JB023780. https://doi.org/10.1029/2021JB023780

[57] ^Florez, M. A., Caporale, M., Buabthong, P., Ross, Z. E., Asimaki, D., & Meier, M.-A. (2022). Data-driven Accelerogram Synthesis using Deep Generative Models. Bulletin of the Seismological Society of America. https://doi.org/10.1785/0120210264

[56] *Liu, Y.-K., Ross, Z. E., Cochran, E. S., & Lapusta, N. (2022). A unified perspective of seismicity and fault coupling along the San Andreas Fault. Science Advances, 8(8), eabk1167. https://doi.org/10.1126/sciadv.abk1167

[55] ^Smith, J. D., Ross, Z. E., Azizzadenesheli, K., & Muir, J. B. (2022). HypoSVI: Hypocenter inversion with Stein variational inference and Physics Informed Neural Networks. Geophysical Journal International, 228, 698–710. https://doi.org/10.1093/gji/ggab309

[54] *Gao, A. F., Castillo, J., Yue, Y., Ross, Z. E., & Bouman, K. L. DeepGEM: Generalized Expectation-Maximization for Blind Inversion. In Advances in neural information processing systems. 34. 2021, 11592–11603.

[53] *Yang, Y., *Gao, A. F., *Castellanos, J. C., Ross, Z. E., Azizzadenesheli, K., & Clayton, R. W. (2021). Seismic wave propagation and inversion with Neural Operators. The Seismic Record, 1(3), 126–134. https://doi.org/10.1785/0320210026

[52] ^Li, B. Q., Smith, J. D., & Ross, Z. E. (2021). Basal nucleation of ascending swarms in Long Valley Caldera. Science Advances, 7(35), eabi8368. https://doi.org/10.1126/sciadv.abi8368

[51] Yu, E., Bhaskaran, A., Chen, S.-L., Ross, Z. E., Hauksson, E., & Clayton, R. W. (2021). Southern California Earthquake Data Now Available in the Amazon AWS Cloud. Seismological Research Letters, 92(5), 3238–3247. https://doi.org/10.1785/0220210039

[50] *Stephenson, O. L., Koehne, T., Zhan, E., Cahill, B. E., Yun, S.-H., Ross, Z. E., & Simons, M. (2021). Deep Learning-based Damage Mapping with InSAR Coherence Time Series. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/TGRS.2021. 3084209

[49] Ross, Z. E., & Cochran, E. S. (2021). Evidence for latent crustal fluid injection transients in Southern California from long-duration earthquake swarms. Geophysical Research Letters, 48(12), e2021GL092465. https://doi.org/10.1029/2021GL092465

[48] Richards, C., Tape, C., Abers, G. A., & Ross, Z. E. (2021). Anisotropy variations in the Alaska subduction zone based on shear-wave splitting from intraslab earthquakes. Geochemistry, Geophysics, Geosystems, 22, e2020GC009558.

[47] Marsan, D., & Ross, Z. E. (2021). Inverse migration of seismicity quiescence during the 2019 Ridgecrest sequence. Journal of Geophysical Research: Solid Earth. https://doi.org/10. 1029/2020JB020329

[46] Hauksson, E., Olson, B., Grant, A., Andrews, J. R., Chung, A. I., Hough, S., Kanamori, H., McBride, S. K., Michael, A., Page, M., Ross, Z. E., Smith, D. E., & Valkaniotis, S. (2021). The Normal Faulting 2020 Mw5.8 Lone Pine Eastern California Earthquake Sequence. Seismological Research Letters. https://doi.org/10.1785/0220200324

[45] Avouac, J. P., Vrain, M., Kim, T., Smith, J., Ader, T., Ross, Z., & Saarno, T. A Convolution Model for Earthquake Forecasting Derived from Seismicity Recorded During the ST1 Geothermal Project on Otaniemi Campus, Finland. In Proceedings world geothermal congress. 2021, 1.

[44] ^Smith, J. D., Azizzadenesheli, K., & Ross, Z. E. (2020). EikoNet: Solving the Eikonal equation with Deep Neural Networks. IEEE Transactions on Geoscience and Remote Sensing, 59(12), 10685–10696. https://doi.org/10.1109/TGRS.2020.3039165

[43] Yeck, W. L., Patton, J. M., Ross, Z. E., Hayes, G. P., Guy, M. R., Ambruz, N. B., Shelly, D. R., Benz, H. M., & Earle, P. S. (2020). Leveraging Deep Learning in Global 24/7 RealTime Earthquake Monitoring at the National Earthquake Information Center. Seismological Research Letters, 92(1), 469–480. https://doi.org/10.1785/0220200178

[42] Schulte-Pelkum, V., Ross, Z. E., Mueller, K., & Ben-Zion, Y. (2020). Tectonic inheritance from deformation fabric in the brittle and ductile southern California crust. Journal of Geophysical Research: Solid Earth, 125(8), e2020JB019525. https://doi.org/10.1029/ 2020JB019525

[41] Ross, Z. E., Cochran, E. S., Trugman, D. T., & Smith, J. D. (2020a). 3D fault architecture controls the dynamism of earthquake swarms. Science, 368(6497). https://doi.org/10.1126/ science.abb0779

[40] Plesch, A., Shaw, J. H., Ross, Z. E., & Hauksson, E. (2020). Detailed 3D fault representations for the 2019 Ridgecrest earthquake sequence. Bulletin of the Seismological Society of America, 110(4), 1818–1831. https://doi.org/10.1785/0120200053

[39] †Zhang, X., *Jia, Z., Ross, Z. E., & Clayton, R. W. (2020). Extracting dispersion curves from ambient noise correlations using deep learning. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/TGRS.2020.2992043

[38] Cochran, E. S., Skoumal, R. J., McPhillips, D., Ross, Z. E., & Keranen, K. M. (2020). Activation of optimally- and unfavorably-oriented faults in a uniform local stress field during the 2011 Prague, Oklahoma, sequence. Geophysical Journal International, ggaa153. https: //doi.org/10.1093/gji/ggaa153

[37] Trugman, D. T., Ross, Z. E., & Johnson, P. A. (2020). Imaging Stress and Faulting Complexity Through Earthquake Waveform Similarity. Geophysical Research Letters, e2019GL085888. https://doi.org/10.1029/2019GL085888

[36] Kanamori, H., Ross, Z. E., & Rivera, L. (2020). Estimation of radiated energy using the KiK-net downhole records–Old method for modern data. Geophysical Journal International, ggaa040. https://doi.org/10.1093/gji/ggaa040

[35] Ross, Z. E., Trugman, D. T., Azizzadenesheli, K., & Anandkumar, A. (2020b). Directivity Modes of Earthquake Populations with Unsupervised Learning. Journal of Geophysical Research: Solid Earth, 125(2), e2019JB018299. https://doi.org/10.1029/2019JB018299

[34] Ross, Z. E., Idini, B., Jia, Z., Stephenson, O. L., Zhong, M., Wang, X., Zhan, Z., Simons, M., Fielding, E. J., Yun, S.-H., Hauksson, E., Moore, A. W., Liu, Z., & Jung, J. (2019a). Hierarchical interlocked orthogonal faulting in the 2019 Ridgecrest earthquake sequence. Science, 366, 346–351. https://doi.org/10.1126/science.aaz0109

[33] Trugman, D. T., & Ross, Z. E. (2019). Pervasive foreshock activity across southern California. Geophysical Research Letters. https://doi.org/10.1029/2019GL083725

[32] Ross, Z. E., Trugman, D. T., Hauksson, E., & Shearer, P. M. (2019b). Searching for Hidden Earthquakes in Southern California. Science, 364(6442). https://doi.org/10.1126/science. aaw6888

[31] Hauksson, E., Ross, Z. E., & Cochran, E. S. (2019). Natural Slow-Growing and ExtendedDuration Seismicity Swarms: Reactivating Joints or Foliations in the Cahuilla Valley Pluton, Central Peninsular Ranges, Southern California. Journal of Geophysical Research: Solid Earth. https://doi.org/10.1029/2019JB017494

[30] Ross, Z. E., Yue, Y., Meier, M.-A., Hauksson, E., & Heaton, T. H. (2019c). PhaseLink: A Deep Learning Approach to Seismic Phase Association. Journal of Geophysical Research: Solid Earth, 124. https://doi.org/10.1029/2018JB016674

[29] Meier, M.-A., Ross, Z. E., Ramachandran, A., Balakrishna, A., Nair, S., Kundzicz, P., Li, Z., Hauksson, E., Andrews, J., & Yue, Y. (2018). Reliable Real-time Seismic Signal/Noise Discrimination with Machine Learning. Journal of Geophysical Research: Solid Earth, 124(1), 788–800. https://doi.org/10.1029/2018JB016661

[28] Kanamori, H., & Ross, Z. E. (2018). Reviving mB. Geophysical Journal International, 216(3). https://doi.org/10.1093/gji/ggy510

[27] Kong, Q., Trugman, D. T., Ross, Z. E., Bianco, M. J., Meade, B. J., & Gerstoft, P. (2018). Machine learning in seismology—Turning data into insights. Seismological Research Letters, 90(1). https://doi.org/10.1785/0220180259

[26] Cochran, E. S., Ross, Z. E., Harrington, R. M., Dougherty, S. M., & Rubenstein, J. L. (2018). Induced earthquake families reveal distinctive evolutionary patterns near disposal wells. Journal of Geophysical Research: Solid Earth, 123, 8045–8055. https://doi.org/10. 1029/2018JB016270

[25] Ross, Z. E., Meier, M.-A., Hauksson, E., & Heaton, T. H. (2018c). Generalized Seismic Phase Detection with Deep Learning. Bulletin of the Seismological Society of America, 108(5A), 2894–2901. https://doi.org/10.1785/0120180080

[24] Ross, Z. E., Meier, M.-A., & Hauksson, E. (2018b). P-wave arrival picking and first-motion polarity determination with deep learning. Journal of Geophysical Research: Solid Earth, 123. https://doi.org/10.1029/2017JB015251

[23] Cheng, Y., Ross, Z. E., & Ben-Zion, Y. (2018). Diverse volumetric faulting patterns in the San Jacinto fault zone. Journal of Geophysical Research: Solid Earth, 123. https://doi.org/ 10.1029/2017JB015408

[22] Ross, Z. E., Kanamori, H., Hauksson, E., & Aso, N. (2018a). Dissipative intraplate faulting during the 2016 Mw 6.2 Tottori, Japan earthquake. Journal of Geophysical Research: Solid Earth, 123(2), 1631–1642. https://doi.org/10.1002/2017JB015077

[21] Qin, L., Ben-Zion, Y., Qiu, H., Share, P.-E., Ross, Z. E., & Vernon, F. L. (2018). Internal structure of the San Jacinto fault zone in the trifurcation area, southeast of Anza, California, from data of dense seismic arrays. Geophysical Journal International, 213(1), 98–114. https: //doi.org/10.1093/gji/ggx540

[20] Yue, H., Ross, Z. E., Liang, C., Michel, S., Fattahi, H., Fielding, E., Moore, A., Liu, Z., & Jia, B. (2017). The 2016 Kumamoto Mw = 7.0 earthquake: a significant event in a faultvolcano system. Journal of Geophysical Research: Solid Earth, 122(11), 9166–9183. https: //doi.org/10.1002/2017JB014525

[19] Allam, A. A., Schulte-Pelkum, V., Ben-Zion, Y., Tape, C., Ruppert, N., & Ross, Z. E. (2017). Ten Kilometer Vertical Moho Offset and Shallow Velocity Contrast Along the Denali Fault from Double-difference Tomography, Receiver Functions, and Fault Zone Head Waves. Tectonophysics, 721, 59–69. https://doi.org/10.1016/j.tecto.2017.09.003

[18] Ross, Z. E., Rollins, C., Cochran, E. S., Hauksson, E., Avouac, J.-P., & Ben-Zion, Y. (2017c). Aftershocks driven by afterslip and fluid pressure sweeping through a fault-fracture mesh. Geophysical Research Letters, 44. https://doi.org/10.1002/2017GL074634

[17] Ross, Z. E., Kanamori, H., & Hauksson, E. (2017b). Anomalously large complete stress drop during the 2016 Mw 5.2 Borrego Springs earthquake inferred by waveform modeling and near-source aftershock deficit. Geophysical Research Letters. https://doi.org/10.1002/ 2017GL073338

[16] Share, P.-E., Ben-Zion, Y., Ross, Z. E., Qiu, H., & Vernon, F. L. (2017). Internal structure of the San Jacinto fault zone at Blackburn Saddle from seismic data of a dense linear array. Geophysical Journal International. https://doi.org/10.1093/gji/ggx191

[15] Qiu, H., Ben-Zion, Y., Ross, Z. E., Share, P.-E., & Vernon, F. L. (2017). Internal structure of the San Jacinto fault zone at Jackass Flat from data recorded by a dense linear array. Geophysical Journal International. https://doi.org/10.1093/gji/ggx096

[14] Ross, Z. E., Hauksson, E., & Ben-Zion, Y. (2017a). Abundant off-fault seismicity and orthogonal structures in the San Jacinto fault zone. Science Advances, 3(3), e1601946. https: //doi.org/10.1126/sciadv.1601946

[13] Hauksson, E., Meier, M.-A., Ross, Z. E., & Jones, L. M. (2017). Evolution of seismicity near the southernmost terminus of the San Andreas Fault: Implications of recent earthquake clusters for earthquake risk in southern California. Geophysical Research Letters, 44. https: //doi.org/10.1002/2016GL072026

[12] Ross, Z. E., Ben-Zion, Y., White, M. C., & Vernon, F. L. (2016a). Analysis of earthquake body wave spectra for potency and magnitude values: Implications for magnitude scaling relations. Geophysical Journal International, 207(2), 1158–1164. https://doi.org/10.1093/ gji/ggw327

[11] Ross, Z. E., White, M. C., Vernon, F. L., & Ben-Zion, Y. (2016b). An improved algorithm for real-time S-wave picking with application to the (augmented) ANZA network in southern California. Bulletin of the Seismological Society of America, 106(5). https://doi.org/10. 1785/0120150230

[10] Ross, Z. E., & Ben-Zion, Y. (2016). Toward reliable automated estimates of earthquake source properties from body wave spectra. Journal of Geophysical Research: Solid Earth, 121(6), 4390–4407. https://doi.org/10.1002/2016JB013003

[9] Wu, F. T., Ross, Z. E., Okaya, D., Ben-Zion, Y., Wang, C.-Y., Kuo-Chen, H., & Liang, W.-T. (2016). Dense Network, Intense Seismicity and Tectonics of Taiwan. Tectonophysics, 692, 152–163. https://doi.org/10.1016/j.tecto.2016.04.025

[8] Okaya, D., Christensen, N., Ross, Z. E., & Wu, F. T. (2016). Terrane-controlled crustal shear wave splitting in Taiwan. Geophysical Research Letters, 43(2). https://doi.org/10. 1002/2015GL066446

[7] Ross, Z. E., & Ben-Zion, Y. (2015). An algorithm for automated identification of fault zone trapped waves. Geophysical Journal International, 202(2), 933–942. https://doi.org/10. 1093/gji/ggv197

[6] Ben-Zion, Y., Vernon, F. L., Ozakin, Y., Zigone, D., Ross, Z. E., Meng, H., White, M., Reyes, J., Hollis, D., & Barklage, M. (2015). Basic data features and results from a spatiallydense seismic array on the San Jacinto fault zone. Geophysical Journal International, 202(1), 370–380. https://doi.org/10.1093/gji/ggv142

[5] Ross, Z. E., Ben-Zion, Y., & Zhu, L. (2015). Isotropic source terms of San Jacinto fault zone earthquakes based on waveform inversions with a generalized CAP method. Geophysical Journal International, 200(2), 1269–1280. https://doi.org/10.1093/gji/ggu460

[4] Ross, Z. E., & Ben-Zion, Y. (2014b). Automatic picking of direct P, S seismic phases and fault zone head waves. Geophysical Journal International, 199(1), 368–381. https://doi.org/ 10.1093/gji/ggu267

[3] Ross, Z. E., & Ben-Zion, Y. (2014a). An Earthquake Detection Algorithm with Pseudo Probabilities of Multiple Indicators. Geophysical Journal International, 197(1), 458–463. https://doi.org/10.1093/gji/ggt516

[2] Ross, Z. E., & Ben-Zion, Y. (2013). Spatio-temporal variations of double-couple aftershock mechanisms and possible volumetric earthquake strain. Journal of Geophysical Research: Solid Earth, 118(5). https://doi.org/10.1002/jgrb.50202

[1] Moss, R. E. S., & Ross, Z. E. (2011). Probabilistic Fault Displacement Hazard Analysis for Reverse Faults. Bulletin of the Seismological Society of America, 101(4). https://doi.org/10. 1785/0120100248

Ross, Z. E., Zhu, W., & Azizzadenesheli, K. (2023). Neural mixture model association of seismic phases.

Sun, H., Yang, Y., Azizzadenesheli, K., Clayton, R. W., & Ross, Z. E. (2022). Accelerating TimeReversal Imaging with Neural Operators for Real-time Earthquake Locations.

Hough, S. E., Ross, Z. E., & Dawson, T. (2020). Introduction to the Special Section on the 2019 Ridgecrest, California, Earthquake Sequence. Bulletin of the Seismological Society of America, 110(4), 1395–1399. https://doi.org/10.1785/0120200201

Ross, Z. E. (2016). Applying automated techniques to large seismic datasets for systematic analyses of phases, source, and structure [Doctoral dissertation, University of Southern California].

Ross, Z. E. (2011). Probabilistic Fault Displacement Hazard Analysis for Reverse Faults and Surface Rupture Scale Invariance [Master's thesis, California Polytechnic State University, San Luis Obispo].

Hough, S. E., Ross, Z. E., and T. Dawson, 2020. Special Section: 2019 Ridgecrest, California, Earthquake Sequence, Bull. Seismol. Soc. Am, 110 (4).