Ying Bi
Impact in
- Artificial Intelligence top 2%
- Evolutionary Algorithms and Applications
- Metaheuristic Optimization Algorithms Research
- Machine Learning and Data Classification
- Biophysics top 5%
- Advanced Fluorescence Microscopy Techniques
Papers in
-
- Evolutionary Algorithms and Applications 44
- Metaheuristic Optimization Algorithms Research 42
- Machine Learning and Data Classification 7
- Reinforcement Learning in Robotics 5
- Co-authors
- Bing Xue (50 shared papers)Mengjie Zhang (46 shared papers)Bo Peng (3 shared papers)Shuting Wan (3 shared papers)Harith Al-Sahaf (2 shared papers)Qi Chen (1 shared paper)Yi Mei (1 shared paper)Binh Tran (1 shared paper)
- Journals
- IEEE Transactions on Evolutionary Computation (16 papers)Applied Soft Computing (7 papers)IEEE Transactions on Cybernetics (5 papers)Journal of the Royal Society of New Zealand (3 papers)IEEE Computational Intelligence Magazine (3 papers)
- Partner nations
- ChinaNew ZealandJapan
In The Last Decade
Ying Bi
88 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 143
- Artificial Intelligence 534
- Biophysics 71
- Computer Vision and Pattern Recognition 173
- Media Technology 70
- Industrial and Manufacturing Engineering 79
Countries citing papers authored by Ying Bi
This map shows the geographic impact of Ying 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 Ying Bi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying Bi more than expected).
Fields of papers citing papers by Ying Bi
This network shows the impact of papers produced by Ying 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 Ying Bi. The network helps show where Ying Bi may publish in the future.
Co-authors
The 25 scholars most cited alongside Ying 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
Showing the 20 most-cited of 106 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 155 | |
| 2 | 2023 | 88 | |
| 3 | 2020 | 67 | |
| 4 | 2022 | 65 | |
| 5 | 2015 | 65 | |
| 6 | 2020 | 56 | |
| 7 | 2022 | 53 | |
| 8 | 2020 | 43 | |
| 9 | 2020 | 42 | |
| 10 | 1996 | 36 | |
| 11 | 2021 | 31 | |
| 12 | 1997 | 29 | |
| 13 | 2022 | 28 | |
| 14 | 2021 | 26 | |
| 15 | 2014 | 25 | |
| 16 | 2015 | 25 | |
| 17 | 2021 | 25 | |
| 18 | 2023 | 24 | |
| 19 | 2021 | 24 | |
| 20 | 2019 | 22 |
About Ying Bi
Ying Bi is a scholar working on Artificial Intelligence, Molecular Biology, Plant Science, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 106 papers that have together received 1.4k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (44 papers), Metaheuristic Optimization Algorithms Research (42 papers), Smart Agriculture and AI (13 papers), Advanced Multi-Objective Optimization Algorithms (12 papers), Machine Learning and Data Classification (7 papers), Reinforcement Learning in Robotics (5 papers), Remote Sensing in Agriculture (4 papers) and Water Quality Monitoring Technologies (4 papers). The work is most often cited by research in Artificial Intelligence (534 citations), Biophysics (71 citations), Computer Vision and Pattern Recognition (173 citations), Media Technology (70 citations) and Industrial and Manufacturing Engineering (79 citations). Ying Bi has collaborated with scholars based in China, New Zealand and Japan. Frequent co-authors include Bing Xue, Mengjie Zhang, Bo Peng, Shuting Wan, Harith Al-Sahaf, Qi Chen, Yi Mei, Binh Tran, Andrew Lensen and Yanan Sun. Their work appears in journals such as IEEE Transactions on Evolutionary Computation, Applied Soft Computing, IEEE Transactions on Cybernetics, Journal of the Royal Society of New Zealand and IEEE Computational Intelligence Magazine.
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.