A-Long Jin

741 citations
24 papers · 510 · h-index 9

Impact in

Papers in

A-Long Jin

21 papers receiving 502 citations

Peers

A-Long Jin
Comparison fields: 5 of 44
  • Computer Networks and Communications 348
  • Computer Science Applications 54
  • Information Systems 165
  • Management Science and Operations Research 59
  • Electrical and Electronic Engineering 186
Replace Tayebeh Bahreini with:
Tayebeh Bahreini United States
Changkun Jiang China
Hamed Shah‐Mansouri Iran
Jinbei Zhang China
Onur Atan United States
Aunas Manzoor South Korea
Xueyi Wang China
Mingyuan Yan United States
Haoran Yu China
A-Long Jin relative to Tayebeh Bahreini United States Tayebeh Bahreini's profile →
Citations per field
00.5×4.8×
Tayebeh Bahreini · 1×
Citations per year

Countries citing papers authored by A-Long Jin

Since Specialization
Citations

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

Fields of papers citing papers by A-Long Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018133
2 2015127
3 2015122
4 202439
5 202114
6 201413
7 201412
8 201610
9 20198
10 20225
11 20144
12 20144
13 20124
14 20144
15 20163
16 20112
17 20231
18 20231
19 20141
20 20161

About A-Long Jin

A-Long Jin is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 24 papers that have together received 510 indexed citations. Recurring topics across this work include Cooperative Communication and Network Coding (12 papers), Advanced MIMO Systems Optimization (8 papers), Topic Modeling (4 papers), Wireless Communication Security Techniques (4 papers), Advanced Wireless Communication Technologies (3 papers), Mobile Ad Hoc Networks (3 papers), Blockchain Technology Applications and Security (2 papers) and Auction Theory and Applications (2 papers). The work is most often cited by research in Computer Networks and Communications (348 citations), Computer Science Applications (54 citations), Information Systems (165 citations), Management Science and Operations Research (59 citations) and Electrical and Electronic Engineering (186 citations). A-Long Jin has collaborated with scholars based in Canada, Hong Kong and China. Frequent co-authors include Wei Song, Dusit Niyato, Ping Wang, Shan Zhang, Xu Li, Xuemin Shen, Qiang Ye, Wei Wang, Shengyu Zhang and Jian Jiao. Their work appears in journals such as IEEE Transactions on Vehicular Technology, Photonics, Journal of Network and Computer Applications, IEEE Transactions on Services Computing and IEEE Transactions on Emerging Topics in Computing.

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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