Jun Yu
Impact in
- Artificial Intelligence top 5%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Artificial Intelligence in Games
- Neural Networks and Applications
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- Advanced Multi-Objective Optimization Algorithms
Papers in
-
- Metaheuristic Optimization Algorithms Research 40
- Evolutionary Algorithms and Applications 28
- Artificial Intelligence in Games 6
- Adversarial Robustness in Machine Learning 3
- Machine Learning and ELM 3
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- Advanced Multi-Objective Optimization Algorithms 19
- Co-authors
- Rui Zhong (28 shared papers)Hideyuki Takagi (14 shared papers)Masaharu Munetomo (10 shared papers)Chao Zhang (15 shared papers)Chengqi Zhang (3 shared papers)Yan Pei (6 shared papers)Fei Peng (3 shared papers)Ying Tan (3 shared papers)
In The Last Decade
Jun Yu
57 papers receiving 348 citations
Peers
Comparison fields: 5 of 64
- Artificial Intelligence 234
- Computational Theory and Mathematics 96
- Industrial and Manufacturing Engineering 27
- Computer Vision and Pattern Recognition 48
- Control and Systems Engineering 36
Countries citing papers authored by Jun Yu
This map shows the geographic impact of Jun Yu'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 Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Yu more than expected).
Fields of papers citing papers by Jun Yu
This network shows the impact of papers produced by Jun Yu. 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 Yu. The network helps show where Jun Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Yu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 42 | |
| 2 | 2023 | 27 | |
| 3 | 2024 | 19 | |
| 4 | 2024 | 15 | |
| 5 | 2024 | 14 | |
| 6 | 2024 | 14 | |
| 7 | 2022 | 12 | |
| 8 | 2024 | 11 | |
| 9 | 2025 | 10 | |
| 10 | 2016 | 10 | |
| 11 | 2023 | 9 | |
| 12 | 2024 | 9 | |
| 13 | 2019 | 9 | |
| 14 | 2023 | 8 | |
| 15 | 2018 | 8 | |
| 16 | 2019 | 8 | |
| 17 | 2019 | 8 | |
| 18 | 2018 | 7 | |
| 19 | 2018 | 6 | |
| 20 | 2024 | 6 |
About Jun Yu
Jun Yu is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Aerospace Engineering and Computer Networks and Communications, having authored 71 papers that have together received 357 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (40 papers), Evolutionary Algorithms and Applications (28 papers), Advanced Multi-Objective Optimization Algorithms (19 papers), Artificial Intelligence in Games (6 papers), Face and Expression Recognition (3 papers), Adversarial Robustness in Machine Learning (3 papers), Evolution and Genetic Dynamics (3 papers) and Machine Learning and ELM (3 papers). The work is most often cited by research in Artificial Intelligence (234 citations), Computational Theory and Mathematics (96 citations), Industrial and Manufacturing Engineering (27 citations), Computer Vision and Pattern Recognition (48 citations) and Control and Systems Engineering (36 citations). Jun Yu has collaborated with scholars based in Japan, China and Egypt. Frequent co-authors include Rui Zhong, Hideyuki Takagi, Masaharu Munetomo, Chao Zhang, Chengqi Zhang, Yan Pei, Fei Peng, Ying Tan, Qinqin Fan and Essam H. Houssein. Their work appears in journals such as Alexandria Engineering Journal, Knowledge-Based Systems, Applied Soft Computing, Scientific Reports and Machine Learning.
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.