Song

133 papers and 764 indexed citations i.

About

Song is a scholar working on Atmospheric Science, Artificial Intelligence and Geophysics. According to data from OpenAlex, Song has authored 133 papers receiving a total of 764 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Atmospheric Science, 38 papers in Artificial Intelligence and 33 papers in Geophysics. Recurrent topics in Song’s work include Geological and Geochemical Analysis (25 papers), Geological and Geophysical Studies (17 papers) and Geochemistry and Geologic Mapping (16 papers). Song is often cited by papers focused on Geological and Geochemical Analysis (25 papers), Geological and Geophysical Studies (17 papers) and Geochemistry and Geologic Mapping (16 papers). Song collaborates with scholars based in and . Song's co-authors include LI -, Zhang, Mao Mao, Zhao Zhao, Liu, Shuguang, Chen, Wang, Gao and Huang and has published in prestigious journals such as International Journal of Technology Management, Earth Science-Journal of China University of Geosciences and 矿业科学技术:英文版.

In The Last Decade

Co-authorship network of co-authors of Song i

Fields of papers citing papers by Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Song. 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 Song. The network helps show where Song may publish in the future.

Countries citing papers authored by Song

Since Specialization
Citations

This map shows the geographic impact of Song'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 Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song more than expected).

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.

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2025