Xiao-Ye Jin
Impact in
- Geophysics top 5%
- Geological and Geochemical Analysis
- earthquake and tectonic studies
- High-pressure geophysics and materials
- Geochemistry and Petrology top 10%
- Geochemistry and Elemental Analysis
Papers in
- Geophysics 18
- Geological and Geochemical Analysis 18
- earthquake and tectonic studies 11
-
- Geochemistry and Geologic Mapping 17
- Co-authors
- Jianwei Li (9 shared papers)Albert H. Hofstra (4 shared papers)Guang Wen (2 shared papers)Xin-Fu Zhao (2 shared papers)Rui Zhu (2 shared papers)Paulo Vasconcelos (1 shared paper)Jian‐xin Zhao (1 shared paper)Yuexing Feng (1 shared paper)
- Journals
- Ore Geology Reviews (5 papers)American Mineralogist (2 papers)Science China Earth Sciences (2 papers)Economic Geology (2 papers)Journal of Earth Science (2 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Xiao-Ye Jin
18 papers receiving 407 citations
Peers
Comparison fields: 5 of 45
- Geophysics 333
- Geochemistry and Petrology 80
- Artificial Intelligence 304
- Media Technology 13
- Analytical Chemistry 12
Countries citing papers authored by Xiao-Ye Jin
This map shows the geographic impact of Xiao-Ye Jin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiao-Ye Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiao-Ye Jin more than expected).
Fields of papers citing papers by Xiao-Ye Jin
This network shows the impact of papers produced by Xiao-Ye Jin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiao-Ye Jin. The network helps show where Xiao-Ye Jin may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiao-Ye Jin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 75 | |
| 2 | 2018 | 57 | |
| 3 | 2021 | 56 | |
| 4 | 2016 | 51 | |
| 5 | 2019 | 32 | |
| 6 | 2020 | 27 | |
| 7 | 2020 | 26 | |
| 8 | 2019 | 23 | |
| 9 | 2011 | 22 | |
| 10 | 2022 | 13 | |
| 11 | 2020 | 11 | |
| 12 | 2021 | 11 | |
| 13 | 2021 | 10 | |
| 14 | 2014 | 9 | |
| 15 | 2024 | 2 | |
| 16 | 2025 | 2 | |
| 17 | 2023 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2024 | 1 |
About Xiao-Ye Jin
Xiao-Ye Jin is a scholar working on Geophysics, Artificial Intelligence, Economics and Econometrics, Geochemistry and Petrology and Computer Networks and Communications, having authored 19 papers that have together received 430 indexed citations. Recurring topics across this work include Geological and Geochemical Analysis (18 papers), Geochemistry and Geologic Mapping (17 papers), earthquake and tectonic studies (11 papers), Geochemistry and Geochronology of Asian Mineral Deposits (4 papers), Geochemistry and Elemental Analysis (3 papers), Vehicular Ad Hoc Networks (VANETs) (1 paper), Radioactive element chemistry and processing (1 paper) and Opportunistic and Delay-Tolerant Networks (1 paper). The work is most often cited by research in Geophysics (333 citations), Geochemistry and Petrology (80 citations), Artificial Intelligence (304 citations), Media Technology (13 citations) and Analytical Chemistry (12 citations). Xiao-Ye Jin has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Jianwei Li, Albert H. Hofstra, Guang Wen, Xin-Fu Zhao, Rui Zhu, Paulo Vasconcelos, Jian‐xin Zhao, Yuexing Feng, Xiao-Dong Deng and Jianzhong Liu. Their work appears in journals such as Ore Geology Reviews, American Mineralogist, Science China Earth Sciences, Economic Geology and Journal of Earth Science.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.