*Corresponding author, #Student advised
X. Si, X. Wu*, Z. Li*, S. Wang, and J. Zhu#, Multi-task multi-station earthquake monitoring: An all-in-one seismic Phase picking, Location, and Association Network(PLAN), submitted.
Hu, Y.#, Z. Li*, F. Lei*, X. Liu, Environment-modulated glacial seismicity near Dalk Glacier in East Antarctica revealed by deep clustering, J. Geophys. Res.- Earth Surface, under review.
Zhu, J.#, L. Fang, F. Miao, L. Fan, J. Zhang, Z. Li*, Deep learning and transfer learning of earthquake and quarry-blast discrimination: Applications to southern California and eastern Kentucky, Geophys. J. Int., under review.
[27] Cui, X.#, Z. Li*, Y. Hu (2023), Similar seismic moment release process for shallow and deep earthquakes, Nature Geoscience, accepted.
[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 rupture 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]
[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:
[4] 李泽峰,断裂带:地震的“老巢”,《中国科学报》,2022-9-19,第1版,要闻. [LINK]
[3] Daniel T. Trugman, Lihua Fang, Jonathan Ajo‐Franklin, Avinash Nayak, Zefeng Li* (2022), Preface to the Focus Section on Big Data Problems in Seismology. Seismological Research Letters 2022;; 93 (5): 2423–2425. doi: https://doi.org/10.1785/0220220219. [LINK]
[2] 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]
[1] Li, Z. (2017), Fault zone imaging and earthquake detection with dense seismic arrays, PhD Thesis at Georgia Institute of Technology. [LINK]