中国科学技术大学-地震数据挖掘研究组 地震数据挖掘实验室
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2021年至今

*Corresponding author, #Student advised/co-advised

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

7. Li, Z.* (2022), A generic model of global earthquake rupture characteristics revealed by machine learning, Geophys. Res. Lett., 49(8), e2021GL096464. [LINK]

6. Li, Z.* (2022), Recent advances in earthquake monitoring II: Emergence of next-generation intelligent systems, Earthquake Sciencedoi: 10.29382/eqs-2021-0054(companion paper with Li, Z., 2021, Earthquake Science)

5. 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]

4.Li, Z.* (2021), 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]

3. 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, e2021GL094698. [LINK][AGU公众号]

2. 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]

1. 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]