Xiangfang Zeng: h-index, Total Citations, and Citation Map
Xiangfang Zeng's h-index is 29 (61 i10-index, 2,771+ total citations across 137+ publications) according to Google Scholar as of May 2026. Xiangfang Zeng is affiliated with Innovation Academy of Precision Measurement Science and Technology, Chinese Academy of Sciences.
Xiangfang Zeng is a researcher affiliated with Innovation Academy of Precision Measurement Science and Technology, Chinese Academy of Sciences, specializing in Seismology. Their work has been cited 2,771 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Xiangfang Zeng's Citation Metrics
Bibliometric impact based on 137 indexed publications. Of these, 19 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 29
- i10-Index
- 61
- Total Citations
- 2,771
- Citing Countries
- 32
As of May 2026.
Xiangfang Zeng has an h-index of 29 and 2,771 total citations across 137 publications, with research cited by institutions in 32 countries.
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Top Cited Works
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Ground motion response to an ML 4.3 earthquake using co-located distributed acoustic sensing and seismometer arrays (vol 213, pg 2020, 2018)
2018245
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Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
1279 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered the application of distributed acoustic sensing arrays for seismic monitoring, establishing foundational methods for noise cross-correlation and ground motion analysis that have been widely adopted by independent scholars.
The researcher pioneered the integration of distributed acoustic sensing with seismometer arrays for ground motion analysis, subsequently advancing automated earthquake detection through deep learning and hybrid methods.
The researcher advanced shallow aftershock analysis and focal mechanism studies in the Wenchuan and Lushan seismic zones, establishing a foundational framework for regional stress field characterization.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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