Xiaoping Jin

1.1k citations
44 papers · 746 · h-index 11

Impact in

    • COVID-19 epidemiological studies
  • Epidemiology top 10%
    • Influenza Virus Research Studies
    • Respiratory viral infections research
    • Mycobacterium research and diagnosis

Papers in

Xiaoping Jin

40 papers receiving 726 citations

Peers

Xiaoping Jin
Comparison fields: 5 of 108
  • Modeling and Simulation 90
  • Epidemiology 320
  • Infectious Diseases 160
  • Environmental Engineering 52
  • Health, Toxicology and Mutagenesis 47
Replace Jasmin S. Kutter with:
Jasmin S. Kutter Netherlands
Chunjie Xu China
Zhongyi Wang China
Zhendong Guo China
Peng Lan China
Yuyang Chen China
Wudi Wei China
Clara Prats Spain
Kaiwei Luo China
Xiaoping Jin relative to Jasmin S. Kutter Netherlands Jasmin S. Kutter's profile →
Citations per field
00.5×7.6×
Jasmin S. Kutter · 1×
Citations per year

Countries citing papers authored by Xiaoping Jin

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoping Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaoping Jin, 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 Xiaoping Jin Line = papers co-authored together Xiaoping Jin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008111
2 2009111
3 2007105
4 201475
5 200771
6 202262
7 202048
8 202123
9 202022
10 201615
11 202311
12 20239
13 20239
14 20238
15 20227
16 20216
17 20225
18 20204
19 20204
20 20104

About Xiaoping Jin

Xiaoping Jin is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Artificial Intelligence, Aerospace Engineering and Epidemiology, having authored 44 papers that have together received 746 indexed citations. Recurring topics across this work include Advanced Wireless Communication Technologies (19 papers), Optical Wireless Communication Technologies (9 papers), Advanced Wireless Communication Techniques (8 papers), Error Correcting Code Techniques (4 papers), PAPR reduction in OFDM (4 papers), Wireless Signal Modulation Classification (3 papers), Cooperative Communication and Network Coding (3 papers) and Influenza Virus Research Studies (3 papers). The work is most often cited by research in Modeling and Simulation (90 citations), Epidemiology (320 citations), Infectious Diseases (160 citations), Environmental Engineering (52 citations) and Health, Toxicology and Mutagenesis (47 citations). Xiaoping Jin has collaborated with scholars based in China, United States and Australia. Frequent co-authors include David K. Shay, Eric Weintraub, W. Thompson, Dan Hasson, Flavia Guillem, Peter E. Warburton, György Abrusán, Chloé Lescale, Xizhong Lou and Ning Jin. Their work appears in journals such as IEEE Transactions on Vehicular Technology, IEEE Wireless Communications Letters, Wireless Personal Communications, IEEE Sensors Journal and IEEE Transactions on Communications.

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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