Song Cheng

24 papers and 437 indexed citations i.

About

Song Cheng is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Song Cheng has authored 24 papers receiving a total of 437 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 10 papers in Atomic and Molecular Physics, and Optics and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Song Cheng’s work include Quantum many-body systems (7 papers), Physics of Superconductivity and Magnetism (4 papers) and Advanced Neural Network Applications (4 papers). Song Cheng is often cited by papers focused on Quantum many-body systems (7 papers), Physics of Superconductivity and Magnetism (4 papers) and Advanced Neural Network Applications (4 papers). Song Cheng collaborates with scholars based in China, United States and Australia. Song Cheng's co-authors include Lei Wang, Tao Xiang, Jing Chen, Haidong Xie, Pan Zhang, Lei Wang, Z. Y. Xie, Rui-Zhen Huang, Zhongchao Wei and Murray T. Batchelor and has published in prestigious journals such as Physical Review Letters, Nuclear Physics B and Physics in Medicine and Biology.

In The Last Decade

Co-authorship network of co-authors of Song Cheng i

Fields of papers citing papers by Song Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Song Cheng

Since Specialization
Citations

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