李泽峰，中国科学技术大学特任研究员，博士生导师，教育部青年长江学者，中科院青年百人计划。2012年中国科学技术大学本科毕业，2017年美国佐治亚理工学院获得博士学位， 2017-2020年美国加州理工学院博士后。主要研究领域是人工智能地震学和分布式光纤地震学。以第一或通讯作者在Nature Geoscience, AGU Advances, GRL，EPSL等期刊发表论文20余篇。近期成果入选ESI高被引论文，AGU亮点，中国光学领域十大社会影响力奖，李善邦青年科技论文奖等。主持国家重点研发计划课题、子课题，国家自然科学基金面上项目。现任JGR-Solid Earth和SRL副主编，地球物理学报、EQS、ERA等期刊编委，中国地震学会地震人工智能专委会副主任、中国地球物理学会地震学专委会副秘书长等。

2020年9月-至今：中国科学技术大学，地球和空间科学学院，特任研究员
2023年6月-2023年9月：日本东京大学，地震研究所，访问教授
2017年9月-2020年8月：美国加州理工学院，地震学实验室，博士后
2012年8月-2017年8月：美国佐治亚理工学院，地球和大气科学系，地球物理学博士
2008年8月-2012年6月：中国科学技术大学，地球和空间科学学院，地球物理学本科

2023年 李善邦青年优秀地震科技论文奖二等奖
2022年 Earthquake Science优秀青年专家论文、优秀编委
2021年 2021中国光学十大社会影响力事件
2020年 中国科学院百人计划青年项目
2016年 佐治亚理工学院地球与大气科学系Kurt Frankel Award
2009-2011年 中国科学技术大学优秀学生奖学金

2023-: 中国地球物理学会地震学专业委员会 副秘书长
2023: JGR-Solid Earth 主编遴选委员会 (Editor-in-Chief Search Committee)
2023-: JGR-Solid Earth 副主编 (Associate Editor)
2022-: 中国地震学会地震人工智能专业委员会 副主任
2022-: RAS Techniques and Instrument 编委
2021-: 地球物理学报 编委
2021-: 中国地震学会青年工作委员会 委员
2021-: Earthquake Science（地震学报英文版）编委
2021-: Earthquake Research Advances 编委
2019-: SRL 副主编 (Associate Editor)

[7] 中华人民共和国科学技术部, 国家重点研发计划课题, 2022YFC3005602, 分布式光纤声波探测方法与衍生灾害监测技术, 2022-11至2025-10, 主持
[6] 国家自然科学基金委员会, 面上项目, 42274063, 基于高精度地震检测的复杂断层余震精细特征研究,2023-01-01至2026-12-31, 主持
[5] 安徽蒙城地球物理国家野外科学观测研究站开放基金, MENGO-202202, 基于全台阵的人工智能地震监测方法和应用, 2023-1至2023-12, 主持. [结题]
[4] 中华人民共和国科学技术部, 国家重点研发计划子课题, 2021YFC3000704-01, 地震数据自动处理系统研发及波速各向异性自动测定, 2021-12至2024-11, 主持
[3] 安徽省科技厅, 安徽省重点研发计划课题, 重点地区地震风险预测和震后应急响应综合系统研发和应用, 2023-2025，主持
[2] 中国科学技术大学, 青年创新重点基金, YT2080002006, 基于分布式光纤的地震监测系统开发, 2021-01至2022-12, 主持. [结题]
[1] 中国地震局地球物理研究所, 基本科研业务费专项, DQJB21Z05, 基于人工智能的地震观测台阵数据自动处理系统研发, 2021-01至2021-12,  参与. [结题]

*Corresponding author, ^#Student advised
Han, X.^#, Z. Li*, F. Liu, J. Li, and H. Yao. Real-time local shear-wave splitting measurement: Application to the vicinity of the Baihetan hydropower plant, Bull. Seismol. Soc. Am., 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.
Peng, G.^#, and Z. Li*. Bimodal modulation of global volcanic eruptions by Earth tides, submitted.
Hu, M.^#, and Z. Li*. DASPy: A Python Toolbox for DAS Seismology, Seismo. Res. Lett., under review.
Liu, G., D. Sun*, and Z. Li. Constraining the geometry of the Northwest Pacific slab using deep clustering of slab guided waves, Seismo. Res. Lett., under review.
吴鹤帅^#, 李泽峰*, 朱俊^#. 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, 在审.
[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., in press. [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 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][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:
[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]