Hai Jin

41 total papers · 875 total citations
26 papers, 560 citations indexed

About

Hai Jin is a scholar working on Computer Networks and Communications, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hai Jin has authored 26 papers receiving a total of 560 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Networks and Communications, 4 papers in Information Systems and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hai Jin's work include IoT and Edge/Fog Computing (4 papers), Caching and Content Delivery (4 papers) and COVID-19 Clinical Research Studies (2 papers). Hai Jin is often cited by papers focused on IoT and Edge/Fog Computing (4 papers), Caching and Content Delivery (4 papers) and COVID-19 Clinical Research Studies (2 papers). Hai Jin collaborates with scholars based in China, Australia and United States. Hai Jin's co-authors include Peng Shu, Jie Yu, Fangming Liu, Bo Li, Di Niu, Min Chen, Victor C. M. Leung, Song Wu, Kun Yang and Xinhou Wang and has published in prestigious journals such as Scientific Reports, IEEE Wireless Communications and IEEE Transactions on Parallel and Distributed Systems.

In The Last Decade

Hai Jin

21 papers receiving 539 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Hai Jin	396	201	176	56	51	26	560
Bo Yin	332 0.8×	136 0.7×	234 1.3×	28 0.5×	70 1.4×	46	537
Ankush Singla	234 0.6×	115 0.6×	57 0.3×	30 0.5×	197 3.9×	30	513
Anjum Naveed	334 0.8×	116 0.6×	164 0.9×	36 0.6×	35 0.7×	45	521
Linfeng Li	246 0.6×	84 0.4×	124 0.7×	68 1.2×	188 3.7×	29	537
J. Amudhavel	239 0.6×	110 0.5×	156 0.9×	63 1.1×	150 2.9×	52	542
Dipanjali Kundu	250 0.6×	191 1.0×	75 0.4×	41 0.7×	233 4.6×	24	668
Yuliang Li	334 0.8×	116 0.6×	188 1.1×	30 0.5×	201 3.9×	31	571
Hamed Tabrizchi	160 0.4×	225 1.1×	43 0.2×	46 0.8×	202 4.0×	23	508
Haiping Zhou	301 0.8×	128 0.6×	70 0.4×	41 0.7×	223 4.4×	21	607
Jinxue Zhang	156 0.4×	213 1.1×	61 0.3×	23 0.4×	170 3.3×	29	552

Countries citing papers authored by Hai Jin

Since Specialization

Citations

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

Fields of papers citing papers by Hai Jin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hai Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Hai Jin. A scholar is included among the top collaborators of Hai Jin 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 Hai Jin. Hai Jin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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