Wu Jun

504 citations
32 papers · 393 · h-index 11

Impact in

Papers in

Wu Jun

28 papers receiving 355 citations

Peers

Wu Jun
Comparison fields: 5 of 49
  • Artificial Intelligence 248
  • Control and Systems Engineering 58
  • Industrial and Manufacturing Engineering 9
  • Leadership and Management 1
  • Sociology and Political Science 28
Replace Yinqiao Xiong with:
Yinqiao Xiong China
Keyvan Ramezanpour United States
Samuel C. Nelson United States
Lanxiao Huang United States
Scott Knight Canada
Daniel S. Dantas United States
J. Girão Germany
Alberto Uriarte United States
Carlo Mazzocca Italy
Wu Jun relative to Yinqiao Xiong China Yinqiao Xiong's profile →
Citations per field
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Citations per year

Countries citing papers authored by Wu Jun

Since Specialization
Citations

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

Fields of papers citing papers by Wu Jun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199899
2 200075
3 199938
4 200023
5
Faculty and student perceptions of academic incivility in the People's Republic of China.
201219
6 202318
7 200215
8 202015
9
Descriptive study of student incivility in the People's Republic of China.
201014
10 202314
11 202111
12 200710
13 20016
14 20096
15 20256
16 20214
17 20224
18 20243
19
Construction and Practice of Practice Base Outside School
20092
20 20112

About Wu Jun

Wu Jun is a scholar working on Control and Systems Engineering, Artificial Intelligence, Media Technology, Architecture and Computer Science Applications, having authored 32 papers that have together received 393 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (6 papers), Machine Fault Diagnosis Techniques (6 papers), Natural Language Processing Techniques (4 papers), Engineering Education and Curriculum Development (2 papers), Workplace Violence and Bullying (2 papers), Higher Education and Teaching Methods (2 papers), Robotic Mechanisms and Dynamics (2 papers) and Forecasting Techniques and Applications (1 paper). The work is most often cited by research in Artificial Intelligence (248 citations), Control and Systems Engineering (58 citations), Industrial and Manufacturing Engineering (9 citations), Leadership and Management (1 citation) and Sociology and Political Science (28 citations). Wu Jun has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Sanjeev P. Khudanpur, Eric Brill, Liping Wang, Cynthia M. Clark, Liping Wang, Zheng-Wen Xu, Hongjun Zhao, Qiang Li, Decheng Wang and Guo Chen. Their work appears in journals such as Applied Sciences, BMC Infectious Diseases, Applied Mathematics and Nonlinear Sciences, IEEE Transactions on Intelligent Transportation Systems and Measurement Science and Technology.

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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