Xiang Fei

100 papers receiving 1.1k citations

Peers

Xiang Fei
Comparison fields: 5 of 121
  • Transportation 214
  • Statistical and Nonlinear Physics 184
  • Building and Construction 198
  • Computer Vision and Pattern Recognition 215
  • Computer Networks and Communications 225
Replace Wei Jin with:
Wei Jin United States
Weiwei Xing China
Yingjie Xia China
T.L. McCluskey United Kingdom
Xiao Luo China
Yuqiang Chen China
Longbiao Chen China
Wenbo He Canada
Xiaoqin Zeng China
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Countries citing papers authored by Xiang Fei

Since Specialization
Citations

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

Fields of papers citing papers by Xiang Fei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiang Fei, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xiang Fei Line = papers co-authored together Xiang Fei links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 114 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201887
2 202187
3 200768
4 201650
5 201345
6 201044
7 200643
8 202243
9 201742
10 202140
11 202239
12 202034
13 201430
14 199729
15 202027
16 201422
17 201822
18 200819
19 200617
20 201817

About Xiang Fei

Xiang Fei is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Control and Systems Engineering and Information Systems, having authored 114 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (12 papers), Complex Network Analysis Techniques (12 papers), Transportation Planning and Optimization (11 papers), Chaos-based Image/Signal Encryption (10 papers), Traffic control and management (9 papers), Traffic Prediction and Management Techniques (9 papers), Text and Document Classification Technologies (8 papers) and Speech and Audio Processing (8 papers). The work is most often cited by research in Transportation (214 citations), Statistical and Nonlinear Physics (184 citations), Building and Construction (198 citations), Computer Vision and Pattern Recognition (215 citations) and Computer Networks and Communications (225 citations). Xiang Fei has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Hani S. Mahmassani, Hanchao Li, Chaobo He, Yong Tang, Pamela Murray‐Tuite, Kuo‐Ming Chao, Zeng Hu, Anne James, Qiu Shui-sheng and Xuesong Zhou. Their work appears in journals such as Transportation Research Part C Emerging Technologies, Future Generation Computer Systems, IEEE Access, Service Oriented Computing and Applications and Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment.

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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