Jingjun Bi
Impact in
- Artificial Intelligence top 5%
- Imbalanced Data Classification Techniques
- Text and Document Classification Technologies
- Anomaly Detection Techniques and Applications
- Machine Learning and Data Classification
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- Artificial Intelligence in Healthcare
Papers in
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- Imbalanced Data Classification Techniques 5
- Advanced Graph Neural Networks 4
- Text and Document Classification Technologies 4
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- Advanced Computing and Algorithms 3
- Co-authors
- Chongsheng Zhang (7 shared papers)Gaojuan Fan (3 shared papers)Baojun Qiao (1 shared paper)Shixin Xu (1 shared paper)Enislay Ramentol (1 shared paper)Hamido Fujita (1 shared paper)Paolo Soda (3 shared papers)Fadi Dornaika (5 shared papers)
In The Last Decade
Jingjun Bi
10 papers receiving 365 citations
Peers
Comparison fields: 5 of 85
- Artificial Intelligence 281
- Health Information Management 36
- Computer Vision and Pattern Recognition 85
- Accounting 27
- Industrial and Manufacturing Engineering 19
Countries citing papers authored by Jingjun Bi
This map shows the geographic impact of Jingjun Bi'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 Jingjun Bi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jingjun Bi more than expected).
Fields of papers citing papers by Jingjun Bi
This network shows the impact of papers produced by Jingjun Bi. 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 Jingjun Bi. The network helps show where Jingjun Bi may publish in the future.
Co-authors
The 15 scholars most cited alongside Jingjun Bi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 160 | |
| 2 | 2019 | 138 | |
| 3 | 2022 | 25 | |
| 4 | 2017 | 18 | |
| 5 | 2023 | 12 | |
| 6 | 2022 | 9 | |
| 7 | 2022 | 7 | |
| 8 | 2025 | 4 | |
| 9 | 2025 | 1 | |
| 10 | 2016 | 1 | |
| 11 | 2025 | 1 | |
| 12 | 2025 | 0 | |
| 13 | 2024 | 0 | |
| 14 | 2025 | 0 |
About Jingjun Bi
Jingjun Bi is a scholar working on Artificial Intelligence, Urban Studies, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Civil and Structural Engineering, having authored 14 papers that have together received 376 indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (5 papers), Advanced Graph Neural Networks (4 papers), Text and Document Classification Technologies (4 papers), Electricity Theft Detection Techniques (3 papers), Face and Expression Recognition (3 papers), Video Surveillance and Tracking Methods (3 papers), Advanced Computing and Algorithms (3 papers) and Ship Hydrodynamics and Maneuverability (2 papers). The work is most often cited by research in Artificial Intelligence (281 citations), Health Information Management (36 citations), Computer Vision and Pattern Recognition (85 citations), Accounting (27 citations) and Industrial and Manufacturing Engineering (19 citations). Jingjun Bi has collaborated with scholars based in China, Spain and Sweden. Frequent co-authors include Chongsheng Zhang, Gaojuan Fan, Baojun Qiao, Shixin Xu, Enislay Ramentol, Hamido Fujita, Paolo Soda, Fadi Dornaika, Salvador García and Weiping Ding. Their work appears in journals such as Applied Intelligence, Knowledge-Based Systems, Information Fusion, Neural Networks and Engineering Applications of Artificial Intelligence.
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.