Hai Jin

About

Hai Jin is a scholar working on Computer Networks and Communications, Epidemiology and Molecular Biology. According to data from OpenAlex, Hai Jin has authored 17 papers receiving a total of 414 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Networks and Communications, 4 papers in Epidemiology and 3 papers in Molecular Biology. Recurrent topics in Hai Jin’s work include Sepsis Diagnosis and Treatment (2 papers), COVID-19 diagnosis using AI (2 papers) and COVID-19 Clinical Research Studies (2 papers). Hai Jin is often cited by papers focused on Sepsis Diagnosis and Treatment (2 papers), COVID-19 diagnosis using AI (2 papers) and COVID-19 Clinical Research Studies (2 papers). Hai Jin collaborates with scholars based in China, United States and Australia. Hai Jin's co-authors include Di Niu, Jie Yu, Bo Li, Peng Shu, Fangming Liu, Min Chen, Victor C. M. Leung, Song Wu, Sheng Di and Shumao Ou and has published in prestigious journals such as Scientific Reports, IEEE Wireless Communications and Frontiers in Cellular and Infection Microbiology.

In The Last Decade

Co-authorship network of co-authors of Hai Jin i

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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.

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).

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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