Jun Zhong

1.5k citations
31 papers · 693 · h-index 15

Impact in

Papers in

Jun Zhong

29 papers receiving 679 citations

Peers

Jun Zhong
Comparison fields: 5 of 119
  • Infectious Diseases 112
  • Cancer Research 88
  • Experimental and Cognitive Psychology 75
  • Human-Computer Interaction 29
  • Cognitive Neuroscience 83
Replace Xinyong Zhang with:
Xinyong Zhang China
Xiaolan Peng China
Teng‐Yi Huang China
Jiyong Ma China
Heather A. Parker New Zealand
Brian C. Haynes United States
Kyle Williams United States
Björn Peters Germany
Alejandro Lopez‐Rincon Netherlands
Xiuhua Peng China
Jun Zhong relative to Xinyong Zhang China Xinyong Zhang's profile →
Citations per field
00.5×7.5×
Xinyong Zhang · 1×
Citations per year

Countries citing papers authored by Jun Zhong

Since Specialization
Citations

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

Fields of papers citing papers by Jun Zhong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014103
2 201579
3 201267
4 201665
5 201842
6 201342
7 201536
8 202236
9 201834
10 201328
11 202125
12 202020
13 201718
14 202015
15 201314
16 202211
17 201310
18 20149
19 20148
20 20236

About Jun Zhong

Jun Zhong is a scholar working on Molecular Biology, Biomedical Engineering, Cognitive Neuroscience, Experimental and Cognitive Psychology and Cardiology and Cardiovascular Medicine, having authored 31 papers that have together received 693 indexed citations. Recurring topics across this work include Non-Invasive Vital Sign Monitoring (6 papers), Robot Manipulation and Learning (4 papers), Tuberculosis Research and Epidemiology (3 papers), Mycobacterium research and diagnosis (3 papers), Evolutionary Psychology and Human Behavior (3 papers), Hand Gesture Recognition Systems (3 papers), RNA and protein synthesis mechanisms (3 papers) and RNA modifications and cancer (3 papers). The work is most often cited by research in Infectious Diseases (112 citations), Cancer Research (88 citations), Experimental and Cognitive Psychology (75 citations), Human-Computer Interaction (29 citations) and Cognitive Neuroscience (83 citations). Jun Zhong has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Jingfa Xiao, Jun Yu, Jiayan Wu, Hong Li, Youxue Zhang, Yaqi Wang, Fei Chen, Wanyi Li, Jie Chen and Qianbao Tan. Their work appears in journals such as Sensors, BMC Genomics, Clinical Infectious Diseases, Journal of Biotechnology and Nature 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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