Quan Fang

55 papers and 1.4k indexed citations i.

About

Quan Fang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Quan Fang has authored 55 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Artificial Intelligence, 17 papers in Computer Vision and Pattern Recognition and 16 papers in Information Systems. Recurrent topics in Quan Fang’s work include Topic Modeling (21 papers), Advanced Graph Neural Networks (15 papers) and Multimodal Machine Learning Applications (12 papers). Quan Fang is often cited by papers focused on Topic Modeling (21 papers), Advanced Graph Neural Networks (15 papers) and Multimodal Machine Learning Applications (12 papers). Quan Fang collaborates with scholars based in China, Saudi Arabia and United States. Quan Fang's co-authors include Changsheng Xu, Shengsheng Qian, Jun Hu, Huaiwen Zhang, Jitao Sang, Xiaowen Huang, Jinguang Wang, Jitao Sang, Ping Guo and Bo Hu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, ACS Nano and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Co-authorship network of co-authors of Quan Fang i

Fields of papers citing papers by Quan Fang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Quan Fang

Since Specialization
Citations

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