*Corresponding author. #Student advised/coadvised.

Manuscripts in process:

Han, X.#, M. Hu#, X. Cui#, Z. Li*. Lander resonance in response to wind and marsquakes as possible origin of InSight's 2.4 Hz seismic noise, submitted.

Peng, G.#, and Z. Li*. Earth Tides as a Dual-Phase Trigger for Volcanic Eruptions Worldwide, submitted.
W. Zhao, F. Wang*, K. Xing, Y. Wang,  Z. Li, and W. Xu. Spatial clustering of deep earthquakes controlled by water carriers, submitted.

Peng, G.#, and Z. Li*. Nucleation conditions of deep-focus earthquakes probed by modulation of Earth’s semidiurnal solid tides, submitted.

Yang, J., H. Zhang*, S. Ni, Z. Li, and X. Bao. Lithosphere Tectonic Regionalization of China and Surrounding Regions from Unsupervised Learning Analysis of Surface Wave Dispersion Data, Seismol. Res. Lett., submitted.

Cui, X.#, Z. Li*, X. Han, and R. Yuan. Spurious sound-speed changes on Mars caused by turbulence-induced pressure frequency variations, Geophys. Res. Lett., submitted.

Ma, S.#, Z. Li*, L. Chen*, J. Shen, Y. Li, W. Wang, and W. Leng. Deciphering Earth’s deep mantle hemispheric geochemical dichotomy with machine learning, submitted.

Published/accepted papers:

[49] Xie, A., Q. Ge, Z. Li, B. Wang, Z. Bao, T. Sun, H. Sun, C. Niu, D. Wang, J. Cheng, Y. Huang, B. Zhu*, Y. Chen*, D. Zhao* (2026). Underwater Distributed Acoustic Sensing of Ship-associated Hydrodynamic Wavefields and Surface Gravity Waves. Seismol. Res. Lett., accepted.

[48] Wang, X., D. Li, J. Zhu, X. Xu*, Z. Li, D. Sandwell, D. Hao, C. Liu, R. Fang(2026). Near Instantaneously Triggered Mw 5.9 Aftershock During the 2025 Mw 7.1 Dingri Earthquake Revealed by Radar Interferometry. Earth Planet. Sci. Lett., 686, 120070. [LINK]

[47] Hu, Y., Cui, X., and Li, Z.* (2026). Mainshock‐induced stress changes modulate initial aftershocks on complex branching faults of the 2019 Ridgecrest earthquake. Geophysical Research Letters, 53, e2026GL122144. [LINK]

[46] Yang, J., H. Zhang*, S. Ni, Z. Li, and X. Bao (2025). Lithosphere Tectonic Regionalization of China and Surrounding Regions from Unsupervised Learning Analysis of Surface Wave Dispersion Data, Seismol. Res. Lett., 97 (3): 2116–2127. [LINK]

[45] Zhao, K., L. Fu*, J. Guo, Y. Hu, Z. Li. K. Lu, R. Wang, X. Hu (2025). Unsupervised Deep Clustering of Microseismic Signals from the Dalk Glacier in East Antarctica, Seismol. Res. Lett., 97 (1): 425–438. [LINK]

[44] 胡敏哲#, 李泽峰* (2025). 基于分布式光纤振动传感的陆地和海底断层快速探测, 科学通报, 70: 5538–5550.[LINK]

[43] Ma, S.#, Z. Li*, D. Sun, Y. Su, J. Li, X. Si, and J. Zhu# (2025). Global Search of PKP Precursors with Graph Neural Network: Implications for Scatterers in the Lowermost mantle, Geophys. Res. Lett., 52, e2025GL115952.[LINK]

[42] Zhao, L., F. Cheng*, J. Xia, Z. Li (2025). Multi-stage Deep Clustering of Urban Ambient Noise for Seismic Imaging,Geophys. J. Int., 242(3), ggaf273. [LINK]

[41] Cui, X.#, Z. Li*, J.-P. Ampuero and L. De Barros (2025). Does foreshock identification depend on seismic monitoring capability?, Geophys. Res. Lett., 52, e2025GL115394. [LINK][AGU公众号]

[40] Ni HY, Li JL*, Yao HJ, Huang XL, Li LL, Zhou DR, Wang XL, Yu SY, Lu YC, Yu JF, Zheng HG, Zhou GL, Zou HW, Yang W, Zhang M, Chen GY, Lin Y, Peng GL, Li ZF and Li HP (2025). Preliminary study of the tectonic structure and seismogenic environment of the M4.7 Feidong earthquake sequence on September 18, 2024 in Hefei. Earthq Sci, 38(3): 234–252. [LINK]

[39] Zhang, J.*, H. Zhu, Z. Li, X. Wu, and J. Zhang (2025). Multi-Station Seismic Location via Machine Learning: Application to Oklahoma and Southern California, Geophys. J. Int.,  241(3), 1853–1867. [LINK]

[38] Sun, H., F. Cheng*, J. Xia, J. Guan, Z. Li, and J. Ajo-Franklin (2025). Unveiling Cryosphere Dynamics by Distributed Acoustic Sensing and Data-driven Hydro-thermal Coupling Simulation, Geophys. Res. Lett., 52, e2024GL111188.[LINK]

[37] 吴鹤帅#, 李泽峰*, 朱俊# (2025). 基于SKS深度学习识别的河北省上地幔各向异性研究, 地球物理学报, 68(4): 1246-1257.[LINK]

[36] Han, X.#, Z. Li*, F. Liu, J. Li, and H. Yao (2025). Real-time local shear-wave splitting measurement: Application to the vicinity of the Bihetan hydropower plant, Bull. Seismol. Soc. Am., 115 (2): 505–515. [LINK]

[35] Liu, G., D. Sun*, and Z. Li (2024). Constraining the geometry of the Northwest Pacific slab using deep clustering of slab guided waves, Seismo. Res. Lett., 96 (1): 310–323. [LINK]

[34] Hu, M.#, and Z. Li* (2024). DASPy: A Python Toolbox for DAS Seismology, Seismo. Res. Lett., 95 (5): 3055–3066. [LINK]

[33] Hu, Y. #, Z. Li*, F. Lei*, X. Liu (2024), Environment-modulated glacial seismicity near Dalk Glacier in East Antarctica revealed by deep clustering, J. Geophys. Res.: Earth Surface, 129, e2023JF007593. [LINK][AGU公众号]

[32] Dong, S., L. Fu*, X. Tang*, Z. Li, and X. Chen (2024). Deep clustering in radar subglacial reflector reveals new subglacial lakes, The Cryosphere, 18, 1241–1257. [LINK]

[31] X. Si, X. Wu*, H. Sheng, J. Zhu#, Z. Li (2024). SeisCLIP: A seismology foundation model pre-trained by multi-modal data for multi-purpose seismic feature extraction, IEEE Transactions on Geoscience and Remote Sensing, 62, 1-13, 5903713. [LINK]

[30] X. Si, X. Wu*, Z. Li*, S. Wang, and J. Zhu# (2024),  An all-in-one seismic Phase picking, Location, and Association Network for multi-task multi-station earthquake monitoring, Communications Earth & Environment, 5, 22. [LINK]

[29] Cui, X.#, Y. Hu#, S. Ma#, Z. Li*, G. Liu, and H. Huang (2024). Bridging supervised and unsupervised learning to build volcano-seismicity classifiers in Kilauea, Hawaii, Seismo. Res. Lett., 95 (3), 1849–1857. [LINK]

[28] Zhu, J.#, L. Fang, F. Miao, L. Fan, J. Zhang, Z. Li* (2024), Deep learning and transfer learning of earthquake and quarry-blast discrimination: Applications to southern California and eastern Kentucky, Geophys. J. Int., 236, 979–993. [LINK]

[27] Cui, X.#, Z. Li*, Y. Hu (2023), Similar seismic moment release process for shallow and deep earthquakes, Nature Geoscience, 16, 454–460. [LINK][科大新闻][科技日报][中国科学报]

[26] Zhang, J., Z. Li, J. Zhang* (2023), Simultaneous Seismic Phase Picking and Polarity Determination with an Attention-based Neural Network, Seismo. Res. Lett., 94 (2A), 813–828. [LINK]

[25] Zhu, J.#, Z. Li*, L. Fang (2023), USTC-Pickers: a Unified Set of seismic phase pickers Transfer learned for China, Earthquake Science, 36(2): 95–112. [LINK]

[24] Ma, S.#, Z. Li*, W. Wang (2022), Machine learning of source spectra for large earthquakes, Geophys. J. Int., 231(1), 692–702.[LINK]

[23]Li, Z.* (2022), A generic model of global earthquake ruptre characteristics revealed by machine learning, Geophys. Res. Lett., 49(8), e2021GL096464.[LINK][AGU公众号][科大新闻][科技日报(头版)][中国科学报(头版)][人民日报客户端][安徽日报][中国新闻网][中安在线][澎湃新闻]

[22] Atterholt, J.*, Z. Zhan, Z. Shen, Z. Li (2022), A unified wavefield-partitioning approach for distributed acoustic sensing, Geophys. J. Int., 228(2), 1410-1418. [LINK]

[21] Li, Z.* (2021b), Recent advances in earthquake monitoring II: Emergence of next-generation intelligent systems, Earthquake Science, 34, doi: 10.29382/eqs-2021-0054. [LINK][Companion paper with #18]

[20] Cui, X#, Z. Li*, and H. Huang (2021), Subdivision of seismicity beneath the summit region of Kilauea volcano: Implications for the preparation process of the 2018 eruption, Geophys. Res. Lett., 48(20), e2021GL094698. [LINK][AGU公众号]

[19] Li, Z.*, Z. Shen, Y. Yang, E. Williams, X. Wang, and Z. Zhan* (2021), Rapid response to the 2019 Ridgecrest earthquake with distributed acoustic sensing, AGU Advances, 2, e2021AV000395, doi: 10.1029/2021AV000395.[LINK][EosHighlight][AGU公众号][科技日报][科学网][2021Light10][科大新闻][AGU Advances Top Cited Paper]

[18] Li, Z.* (2021a), Recent advances in earthquake monitoring I: Ongoing revolution of seismic instrumentation, Earthquake Science, 34(2), 177-188, doi: 10.29382/eqs-2021-0011. [LINK][EQS公众号][EQS优秀青年专家论文]

[17] Yin, J., Z. Li*, M. Denolle (2021), Source time function clustering reveals patterns in earthquake dynamics, Seismo. Res. Lett., 92, 2343-2353, doi:10.1785/0220200403. [LINK]

[16] Cheng, Y.*, Y. Ben-Zion, F. Brenguier, C. W. Johnson, Z. Li, P. Share, and F. Vernon (2020), An automated method for developing a catalog of small earthquakes using data of a dense seismic array and nearby stations, Seismo. Res. Lett., 91(5), 2862-2871, doi: 10.1785/0220200134. [LINK]

[15] Li, Z.^*, E. Hauksson, and J. Andrews (2019), Methods for amplitude calibration and orientation discrepancy measurement: Comparing co-located sensors of different types in Southern California Seismic Network, Bull. Seismol. Soc. Am., 109(4), 1563–1570, doi: 10.1785/0120190019. [LINK]

[14] Zhu, L.*, Z. Peng, J. McClellan, C. Li, D. Yao, Z. Li., and L. Fang (2019), Deep learning for seismic phase detection and picking in the aftershock zone of the 2008 Mw 7.9 Wenchuan Earthquake, Phys. Earth Planet. Inter., 293, 106261, doi: 10.1016/j.pepi.2019.05.004. [LINK]

[13] Li, Z.^*, E. Hauksson, T. Heaton, L. Rivera, and J. Andrews (2019), Monitoring data quality by comparing co-located broadband and strong-motion waveforms in Southern California Seismic Network, Seismo. Res. Lett., 90(2A), 699-707, doi: 10.1785/0220180331. [LINK]

[12] Meier, M.-A.*, Z. Ross, A. Ramachandran, A. Balakrishna, S. Nair, P. Kundzicz, Z. Li, E. Hauksson, J. Andrews (2019), Reliable real-time seismic signal/noise discrimination with machine learning, J. Geophys. Res. Solid Earth, 124, 788-800, doi:10.1029/2018JB016661. [LINK]

[11] Li, Z.^*, and Z. Zhan (2018), Pushing the limit of earthquake detection with distributed acoustic sensing and template matching: A case study at the Brady geothermal field, Geophys. J. Int., 215, 1583-1593, doi: 10.1093/gji/ggy359. [LINK]

[10] Li, C.*, Z. Li, Z. Peng, C. Zhang, N. Nakata, and T. Sickbert (2018), Long-period long-duration events detected by the IRIS community wavefield demonstration experiment in Oklahoma: Tremor or train signals?, Seismo. Res. Lett., 89, 1641-1651, doi: 10.1785/02201080081. [LINK]

[9] Li, Z.^*, M.-A. Meier, E. Hauksson, Z. Zhan, and J. Andrews (2018), Machine learning seismic wave discrimination: Application to earthquake early warning, Geophys. Res. Lett., 45, 4773-4779. doi: 10.1029/2018GL077870. [LINK]

[8] Li, Z.^*, Z. Peng, D. Hollis, L. Zhu, J. McClellan (2018), High-resolution seismic event detection using local similarity for Large-N arrays, Sci. Rep., 8, 1646. doi:10.1038/s41598-018-19728-w. [LINK]

[7] Li, Z.^*, and Z. Peng (2017), Stress- and structure-induced anisotropy in Southern California from two-decades of shear-wave splitting measurements, Geophys. Res. Lett., 44, 9607-9614. doi: 10.1002/2017GL075163. [LINK]

[6] Li, Z.^*, and Z. Peng (2016), An automatic phase picker for local earthquakes with predetermined locations: Combining a signal-to-noise ratio detector with 1D velocity model inversion, Seismol. Res. Lett., 87(6), 1397-1405, doi: 10.1785/0220160027. [LINK]

[5] Li, Z.^*, and Z. Peng (2016), Automatic identification of fault zone head waves and direct P waves and its application in the Parkfield section of the San Andreas Fault, California, Geophys. J. Int., 250, 1326-1341, doi: 10.1093/gji/ggw082. [LINK]

[4] Li, Z.^*, Z. Peng, Y. Ben-Zion, and F. Vernon (2015), Spatial variations of shear-wave anisotropy near the San Jacinto Fault Zone in southern California, J. Geophys. Res. Solid Earth, 120, 8334-8347, doi: 10.1002/2015JB012483. [LINK]

[3] Yang, W.,* Z. Peng, B. Wang, Z. Li, and S. Yuan (2015), Velocity contrast along the rupture zone of the 2010 Mw6.9 Yushu, China earthquake from systematic analysis of fault zone head waves, Earth Planet. Sci. Lett., 416, 91-97, doi: 10.1016/j.epsl.2015.01.043. [LINK]

[2] Yang, H.*, Z. Li, Z. Peng, Y. Ben-Zion, and F. Vernon (2014), Low velocity zones along the San Jacinto Fault, Southern California, from body waves recorded in dense linear arrays, J. Geophys. Res. Solid Earth, 119, 8976-8990, doi: 10.1002/2014JB011548. [LINK]

[1] Li, Z., H. Zhang*, and Z. Peng (2014), Structure-controlled seismic anisotropy along the Karadere-Duzce branch of the north Anatolian fault revealed by shear-wave splitting tomography, Earth Planet. Sci. Lett., 391, 319-326, doi: 10.1016/j.epsl.2014.01.046. [LINK]

Non-peer-reviewed:

1. Bergen, K., T. Yang, and Z. Li (2019), Preface to the Focus Section on Machine Learning in Seismology. Seismological Research Letters, 90 (2A): 477–480. doi: https://doi.org/10.1785/0220190018 [LINK]

2. Li, Z. (2017), Fault zone imaging and earthquake detection with dense seismic arrays, PhD Thesis at Georgia Institute of Technology. [LINK]