Song Bian

10 total papers · 463 total citations
3 papers, 43 citations indexed

About

Song Bian is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Song Bian has authored 3 papers receiving a total of 43 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Statistical and Nonlinear Physics. Recurrent topics in Song Bian’s work include Advanced Graph Neural Networks (2 papers), Graph Theory and Algorithms (1 paper) and Image and Video Quality Assessment (1 paper). Song Bian is often cited by papers focused on Advanced Graph Neural Networks (2 papers), Graph Theory and Algorithms (1 paper) and Image and Video Quality Assessment (1 paper). Song Bian collaborates with scholars based in Hong Kong, Singapore and China. Song Bian's co-authors include Jeffrey Xu Yu, Sibo Wang, Hao Ding, Yunjun Gao, Yizhou Sun, Lei Liang, Wei Wang, Ting Chen, Yunsheng Bai and Lu Chen and has published in prestigious journals such as Proceedings of the VLDB Endowment, ACM Transactions on Knowledge Discovery from Data and arXiv (Cornell University).

Co-authorship network of co-authors of Song Bian

This figure shows the co-authorship network connecting the top 25 collaborators of Song Bian. A scholar is included among the top collaborators of Song Bian based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Song Bian. Song Bian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

Song Bian

3 papers receiving 43 citations

Fields of papers citing papers by Song Bian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Song Bian

Since Specialization
Citations

This map shows the geographic impact of Song Bian'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 Bian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song Bian 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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2026