Qingyun Dai
- Industrial and Manufacturing Engineering top 0.2%
- Management Information Systems top 2%
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 1%
- Artificial Intelligence top 5%
- Co-authors
- George Q. HuangRay Y. ZhongXu ChenTing QuShulin LanGuiping HuBingo Wing‐Kuen LingFangyuan Lei
- Topics
- Advanced Manufacturing and Logistics Optimization (12 papers)Scheduling and Optimization Algorithms (11 papers)Image and Signal Denoising Methods (10 papers)
- Journals
- Journal of Applied PhysicsIEEE Transactions on Geoscience and Remote SensingIEEE Transactions on Signal Processing
- Partner nations
- ChinaHong KongUnited Kingdom
In The Last Decade
Qingyun Dai
98 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Industrial and Manufacturing Engineering 948
- Management Information Systems 366
- Computer Vision and Pattern Recognition 283
- Media Technology 268
- Artificial Intelligence 218
Countries citing papers authored by Qingyun Dai
This map shows the geographic impact of Qingyun Dai'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 Qingyun Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingyun Dai more than expected).
Fields of papers citing papers by Qingyun Dai
This network shows the impact of papers produced by Qingyun Dai. 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 Qingyun Dai. The network helps show where Qingyun Dai may publish in the future.
Co-authorship network of co-authors of Qingyun Dai
This figure shows the co-authorship network connecting the top 25 collaborators of Qingyun Dai. A scholar is included among the top collaborators of Qingyun Dai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Qingyun Dai. Qingyun Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 4 | |
| 8 | 6 | |
| 9 | 5 | |
| 10 | 2 | |
| 11 | 8 | |
| 12 | 14 | |
| 13 | 37 | |
| 14 | 16 | |
| 15 | 2 | |
| 16 | 31 | |
| 17 | 4 | |
| 18 | 0 | |
| 19 | 2 | |
| 20 | 36 |
About Qingyun Dai
Qingyun Dai is a scholar working on Industrial and Manufacturing Engineering, Computer Vision and Pattern Recognition and Signal Processing, having authored 108 papers that have together received 2.1k indexed citations. Recurring topics across this work include Advanced Manufacturing and Logistics Optimization (12 papers), Scheduling and Optimization Algorithms (11 papers) and Image and Signal Denoising Methods (10 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (948 citations), Management Information Systems (366 citations) and Media Technology (268 citations). Qingyun Dai has collaborated with scholars based in China, Hong Kong and United Kingdom. Frequent co-authors include George Q. Huang, Ray Y. Zhong, Xu Chen, Ting Qu, Shulin Lan, Guiping Hu, Bingo Wing‐Kuen Ling, Shulin Lan, Fangyuan Lei and Hao Wu. Their work appears in journals such as Journal of Applied Physics, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Signal Processing.
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.