Qingtao Pan
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Aerospace Engineering top 10%
- Control and Systems Engineering top 10%
- Computer Networks and Communications top 10%
- Co-authors
- Jun TangGang LiuSongyang LaoHao LiFeng ZhuGuoli YangXi ChenXiaomin Zhu
- Topics
- Metaheuristic Optimization Algorithms Research (7 papers)Complex Network Analysis Techniques (6 papers)Advanced Multi-Objective Optimization Algorithms (3 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionIndustrial and Manufacturing Engineering
- Journals
- Expert Systems with ApplicationsInformation SciencesIEEE Transactions on Aerospace and Electronic Systems
- Partner nations
- ChinaUnited States
In The Last Decade
Qingtao Pan
16 papers receiving 673 citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Artificial Intelligence 243
- Computer Vision and Pattern Recognition 143
- Aerospace Engineering 141
- Control and Systems Engineering 114
- Computer Networks and Communications 109
Countries citing papers authored by Qingtao Pan
This map shows the geographic impact of Qingtao Pan'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 Qingtao Pan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingtao Pan more than expected).
Fields of papers citing papers by Qingtao Pan
This network shows the impact of papers produced by Qingtao Pan. 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 Qingtao Pan. The network helps show where Qingtao Pan may publish in the future.
Co-authorship network of co-authors of Qingtao Pan
This figure shows the co-authorship network connecting the top 25 collaborators of Qingtao Pan. A scholar is included among the top collaborators of Qingtao Pan 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 Qingtao Pan. Qingtao Pan 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 | 6 | |
| 4 | 4 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 7 | |
| 8 | 32 | |
| 9 | 2 | |
| 10 | 0 | |
| 11 | 2 | |
| 12 | 3 | |
| 13 | 0 | |
| 14 | 5 | |
| 15 | 14 | |
| 16 | 22 | |
| 17 | 17 | |
| 18 | 13 | |
| 19 | A Review on Representative Swarm Intelligence Algorithms for Solving Optimization Problems: Applications and Trendsbreakdown → | 555 |
| 20 | 3 |
About Qingtao Pan
Qingtao Pan is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Modeling and Simulation, having authored 20 papers that have together received 689 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (7 papers), Complex Network Analysis Techniques (6 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). The work is most often cited by research in Artificial Intelligence (243 citations), Computer Vision and Pattern Recognition (143 citations) and Industrial and Manufacturing Engineering (69 citations). Qingtao Pan has collaborated with scholars based in China and United States. Frequent co-authors include Jun Tang, Gang Liu, Jun Tang, Songyang Lao, Hao Li, Feng Zhu, Guoli Yang, Xi Chen, Xiaomin Zhu and Yutong Yuan. Their work appears in journals such as Expert Systems with Applications, Information Sciences and IEEE Transactions on Aerospace and Electronic Systems.
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.