Gaifang Dong
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- Vehicle Routing Optimization Methods 4
- Microbiology top 10%
- Antimicrobial Peptides and Activities 4
- Artificial Intelligence top 10%
- Metaheuristic Optimization Algorithms Research 6
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- Advanced Multi-Objective Optimization Algorithms 3
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- Machine Learning in Bioinformatics 6
- Genomics and Phylogenetic Studies 4
- Biochemical and Structural Characterization 4
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- Probiotics and Fermented Foods 3
- Co-authors
- William GuoKevin S. TickleHonghui LiPengfei XieYujia HuoJie ZhangChen LiYongchun Zuo
- Journals
- SHILAP Revista de lepidopterología (2 papers)Expert Systems with Applications (2 papers)Briefings in Bioinformatics (1 paper)
In The Last Decade
Gaifang Dong
19 papers receiving 258 citations
Peers
Comparison fields: 5 of 73
- Industrial and Manufacturing Engineering 81
- Microbiology 36
- Artificial Intelligence 112
- Computational Theory and Mathematics 32
- Computer Vision and Pattern Recognition 31
Countries citing papers authored by Gaifang Dong
This map shows the geographic impact of Gaifang Dong'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 Gaifang Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gaifang Dong more than expected).
Fields of papers citing papers by Gaifang Dong
This network shows the impact of papers produced by Gaifang Dong. 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 Gaifang Dong. The network helps show where Gaifang Dong may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gaifang Dong, 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 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 7 | |
| 4 | 2023 | 25 | |
| 5 | 2023 | 1 | |
| 6 | 2022 | 0 | |
| 7 | 2022 | 14 | |
| 8 | 2021 | 22 | |
| 9 | 2018 | 1 | |
| 10 | 2018 | 4 | |
| 11 | 2018 | 8 | |
| 12 | 2017 | 2 | |
| 13 | 2017 | 3 | |
| 14 | 2016 | 22 | |
| 15 | 2016 | 46 | |
| 16 | 2016 | 1 | |
| 17 | 2015 | 3 | |
| 18 | 2012 | 14 | |
| 19 | 2011 | 82 | |
| 20 | 2010 | 2 |
About Gaifang Dong
Gaifang Dong is a scholar working on Microbiology, Human Factors and Ergonomics and Industrial and Manufacturing Engineering, having authored 22 papers that have together received 265 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (6 papers), Metaheuristic Optimization Algorithms Research (6 papers), Antimicrobial Peptides and Activities (4 papers), Vehicle Routing Optimization Methods (4 papers), Genomics and Phylogenetic Studies (4 papers), Biochemical and Structural Characterization (4 papers), Advanced Multi-Objective Optimization Algorithms (3 papers) and Probiotics and Fermented Foods (3 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (81 citations), Microbiology (36 citations) and Artificial Intelligence (112 citations). Gaifang Dong has collaborated with scholars based in China and Australia. Frequent co-authors include William Guo, Kevin S. Tickle, Honghui Li, Pengfei Xie, Yujia Huo, Jie Zhang, Chen Li, Yongchun Zuo, Lei Zheng and Jing Gao. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Briefings in Bioinformatics.
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.