Ke Li
Impact in
- Computational Theory and Mathematics top 0.05%
- Advanced Multi-Objective Optimization Algorithms
- Artificial Intelligence top 0.2%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
Papers in
-
- Advanced Multi-Objective Optimization Algorithms 56
-
- Metaheuristic Optimization Algorithms Research 52
- Evolutionary Algorithms and Applications 37
- Speech Recognition and Synthesis 10
- Topic Modeling 9
- Natural Language Processing Techniques 7
Ke Li
199 papers receiving 4.8k citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Computational Theory and Mathematics 2.9k
- Artificial Intelligence 3.2k
- Management Science and Operations Research 669
- Industrial and Manufacturing Engineering 259
- Software 79
Countries citing papers authored by Ke Li
This map shows the geographic impact of Ke 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 Ke Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ke Li more than expected).
Fields of papers citing papers by Ke Li
This network shows the impact of papers produced by Ke 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 Ke Li. The network helps show where Ke Li may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ke Li, 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 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2025 | 1 | |
| 6 | 2025 | 0 | |
| 7 | 2024 | 5 | |
| 8 | 2024 | 9 | |
| 9 | 2024 | 6 | |
| 10 | 2024 | 7 | |
| 11 | 2024 | 11 | |
| 12 | 2024 | 10 | |
| 13 | 2024 | 6 | |
| 14 | 2023 | 2 | |
| 15 | 2023 | 16 | |
| 16 | 2022 | 99 | |
| 17 | 2022 | 19 | |
| 18 | 2021 | 31 | |
| 19 | 2021 | 18 | |
| 20 | The Research Review on the Topic about Training Top-notch Innovative Talents for Recent 10 Years | 2013 | 0 |
About Ke Li
Ke Li is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Computer Vision and Pattern Recognition, Software and Signal Processing, having authored 230 papers that have together received 5.0k indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (56 papers), Metaheuristic Optimization Algorithms Research (52 papers), Evolutionary Algorithms and Applications (37 papers), Optimal Experimental Design Methods (10 papers), Speech Recognition and Synthesis (10 papers), Topic Modeling (9 papers), Natural Language Processing Techniques (7 papers) and Software Engineering Research (7 papers). The work is most often cited by research in Computational Theory and Mathematics (2.9k citations), Artificial Intelligence (3.2k citations), Management Science and Operations Research (669 citations), Industrial and Manufacturing Engineering (259 citations) and Software (79 citations). Ke Li has collaborated with scholars based in China, United Kingdom and Hong Kong. Frequent co-authors include Sam Kwong, Qingfu Zhang, Kalyanmoy Deb, Xin Yao, Renzhi Chen, Guangtao Fu, Miqing Li, Ran Wang, Álvaro Fialho and Mengyuan Wu. Their work appears in journals such as IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, Information Sciences, Neurocomputing and Swarm and Evolutionary Computation.
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.