Guangyao Li
- Computational Theory and Mathematics top 5%
- Artificial Intelligence
- Mechanical Engineering
- Civil and Structural Engineering top 10%
- Statistics, Probability and Uncertainty top 5%
- Topics
- Advanced Multi-Objective Optimization Algorithms (13 papers)Probabilistic and Robust Engineering Design (6 papers)Advanced Graph Neural Networks (6 papers)
- Cited by
- Statistics, Probability and UncertaintyComputational Theory and MathematicsManagement Science and Operations Research
- Journals
- SHILAP Revista de lepidopterologíaComputer Physics CommunicationsIEEE Transactions on Neural Networks and Learning Systems
- Partner nations
- ChinaCanadaUnited Kingdom
In The Last Decade
Guangyao Li
27 papers receiving 306 citations
Peers
Comparison fields: 5 of 63
- Computational Theory and Mathematics 111
- Artificial Intelligence 83
- Mechanical Engineering 74
- Civil and Structural Engineering 73
- Statistics, Probability and Uncertainty 70
Countries citing papers authored by Guangyao Li
This map shows the geographic impact of Guangyao Li'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 Guangyao Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guangyao Li more than expected).
Fields of papers citing papers by Guangyao Li
This network shows the impact of papers produced by Guangyao Li. 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 Guangyao Li. The network helps show where Guangyao Li may publish in the future.
Co-authorship network of co-authors of Guangyao Li
This figure shows the co-authorship network connecting the top 25 collaborators of Guangyao Li. A scholar is included among the top collaborators of Guangyao Li 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 Guangyao Li. Guangyao Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 33 | |
| 5 | 0 | |
| 6 | 12 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 7 | |
| 10 | 1 | |
| 11 | 19 | |
| 12 | 14 | |
| 13 | 14 | |
| 14 | 16 | |
| 15 | 2 | |
| 16 | 6 | |
| 17 | 4 | |
| 18 | 6 | |
| 19 | 5 | |
| 20 | 3 |
About Guangyao Li
Guangyao Li is a scholar working on Computational Theory and Mathematics, Statistics, Probability and Uncertainty and Management Science and Operations Research, having authored 29 papers that have together received 314 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (13 papers), Probabilistic and Robust Engineering Design (6 papers) and Advanced Graph Neural Networks (6 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (70 citations), Computational Theory and Mathematics (111 citations) and Management Science and Operations Research (43 citations). Guangyao Li has collaborated with scholars based in China, Canada and United Kingdom. Frequent co-authors include Hu Wang, Enying Li, Wei Hu, Libin Duan, Aiguo Cheng, Zhaohui Hu, Ning‐Cong Xiao, Fan Ye, Zequn Sun and G. Gary Wang. Their work appears in journals such as SHILAP Revista de lepidopterología, Computer Physics Communications and IEEE Transactions on Neural Networks and Learning 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.