Chao Qian
- Artificial Intelligence top 2%
- Computational Theory and Mathematics top 1%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Management Science and Operations Research top 5%
- Topics
- Metaheuristic Optimization Algorithms Research (38 papers)Advanced Multi-Objective Optimization Algorithms (37 papers)Evolutionary Algorithms and Applications (31 papers)
- Cited by
- Computational Theory and MathematicsArtificial IntelligenceManagement Science and Operations Research
- Partner nations
- ChinaGermanyUnited Kingdom
In The Last Decade
Chao Qian
77 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 98
- Artificial Intelligence 728
- Computational Theory and Mathematics 557
- Computer Networks and Communications 148
- Computer Vision and Pattern Recognition 138
- Management Science and Operations Research 108
Countries citing papers authored by Chao Qian
This map shows the geographic impact of Chao Qian'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 Chao Qian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chao Qian more than expected).
Fields of papers citing papers by Chao Qian
This network shows the impact of papers produced by Chao Qian. 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 Chao Qian. The network helps show where Chao Qian may publish in the future.
Co-authorship network of co-authors of Chao Qian
This figure shows the co-authorship network connecting the top 25 collaborators of Chao Qian. A scholar is included among the top collaborators of Chao Qian 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 Chao Qian. Chao Qian 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 | Reducing the uncertainty in estimating soil microbial-derived carbon storagebreakdown → | 68 |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 2 | |
| 9 | 2 | |
| 10 | 22 | |
| 11 | 0 | |
| 12 | 5 | |
| 13 | 3 | |
| 14 | ZOOpt/ZOOjl: Toolbox for Derivative-Free Optimization. | 1 |
| 15 | 30 | |
| 16 | Subset Selection under Noise | 22 |
| 17 | Parallel pareto optimization for subset selection | 21 |
| 18 | On constrained boolean pareto optimization | 19 |
| 19 | Subset selection by Pareto optimization | 83 |
| 20 | 77 |
About Chao Qian
Chao Qian is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Management Science and Operations Research, having authored 85 papers that have together received 1.2k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (38 papers), Advanced Multi-Objective Optimization Algorithms (37 papers) and Evolutionary Algorithms and Applications (31 papers). The work is most often cited by research in Computational Theory and Mathematics (557 citations), Artificial Intelligence (728 citations) and Management Science and Operations Research (108 citations). Chao Qian has collaborated with scholars based in China, Germany and United Kingdom. Frequent co-authors include Zhi‐Hua Zhou, Yang Yu, Ke Tang, Chao Bian, Yang Yu, Jing-Cheng Shi, Xin Yao, Chunhui Jiang, Wenjing Hong and Miqing Li. Their work appears in journals such as Proceedings of the National Academy of Sciences, Information Sciences and Artificial Intelligence.
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.