*Corresponding author, ^#Student advised/co-advised; Bold titles for recent highlights

8. Li, Z.*, A generic spectrum of global earthquake rupture characteristics revealed by machine learning, in revision for Geophys. Res. Lett. [LINK]

7. Ma, S.^#, Li, Z.*, W. Wang, Machine learning of source spectra for large earthquakes, in revision for Geophys. J. Int.[LINK]

5. Li, Z.* (2022), Recent advances in earthquake monitoring II: Emergence of next-generation intelligent systems, Earthquake Science, accepted.(companion paper with #21)

5.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]

4. 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]

3. Atterholt, J.*, Z. Zhan, Z. Shen, Z. Li (2021), A unified wavefield-partitioning approach for distributed acoustic sensing, Geophys. J. Int., 228(2), 1410-1418. [LINK]

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]