Hua Jin

60 total papers · 1.9k total citations
43 papers, 1.5k citations indexed

About

Hua Jin is a scholar working on Statistics and Probability, Management Science and Operations Research and Epidemiology. According to data from OpenAlex, Hua Jin has authored 43 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Statistics and Probability, 8 papers in Management Science and Operations Research and 7 papers in Epidemiology. Recurrent topics in Hua Jin's work include Statistical Methods and Inference (12 papers), Advanced Statistical Methods and Models (10 papers) and Statistical Methods in Clinical Trials (10 papers). Hua Jin is often cited by papers focused on Statistical Methods and Inference (12 papers), Advanced Statistical Methods and Models (10 papers) and Statistical Methods in Clinical Trials (10 papers). Hua Jin collaborates with scholars based in China, United States and Canada. Hua Jin's co-authors include Igor Grant, David P. Salmon, Elena S. H. Yu, Paul S. Levy, Melville R. Klauber, Mingyuan Zhang, William T. Liu, Guojun Cai, Robert Katzman and Zhenyu Wang and has published in prestigious journals such as Annals of Neurology, Scientific Reports and Biometrics.

In The Last Decade

Hua Jin

43 papers receiving 1.4k citations

Hit Papers

The prevalence of dementi... 1990 2026 2002 2014 1990 250 500 750

Author Peers

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

Author Last Decade Papers Cites
Hua Jin 621 316 166 166 153 43 1.5k
Adam Ciarleglio 314 0.5× 118 0.4× 154 0.9× 56 0.3× 352 2.3× 53 1.3k
Steven Sevush 520 0.8× 366 1.2× 59 0.4× 61 0.4× 385 2.5× 34 1.3k
Norbert Benda 231 0.4× 153 0.5× 302 1.8× 208 1.3× 74 0.5× 83 1.8k
J. Scott Andrews 768 1.2× 540 1.7× 55 0.3× 26 0.2× 140 0.9× 44 1.4k
Mark Belger 762 1.2× 144 0.5× 132 0.8× 124 0.7× 39 0.3× 83 1.7k
Silvan Licher 569 0.9× 407 1.3× 173 1.0× 18 0.1× 72 0.5× 41 1.6k
Willa D. Brenowitz 607 1.0× 658 2.1× 125 0.8× 20 0.1× 213 1.4× 64 1.6k
Kazushi Maruo 201 0.3× 162 0.5× 67 0.4× 136 0.8× 193 1.3× 186 1.4k
Michael Happich 379 0.6× 266 0.8× 194 1.2× 20 0.1× 72 0.5× 60 1.7k
Allison Caban‐Holt 410 0.7× 317 1.0× 83 0.5× 21 0.1× 193 1.3× 58 1.4k

Countries citing papers authored by Hua Jin

Since Specialization
Citations

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

Fields of papers citing papers by Hua Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hua Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Hua Jin. A scholar is included among the top collaborators of Hua 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 Hua Jin. Hua 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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