Shenkai Gu
Impact in
- Artificial Intelligence top 5%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Machine Learning and Data Classification
- Imbalanced Data Classification Techniques
- Machine Learning and ELM
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- Advanced Multi-Objective Optimization Algorithms
Papers in
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- Metaheuristic Optimization Algorithms Research 3
- Machine Learning and Data Classification 2
- Anomaly Detection Techniques and Applications 2
- Evolutionary Algorithms and Applications 2
- Domain Adaptation and Few-Shot Learning 1
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- Software System Performance and Reliability 1
- Energy Efficient Wireless Sensor Networks 1
- Co-authors
- Yaochu Jin (5 shared papers)Ran Cheng (2 shared papers)Li Cheng (1 shared paper)Xiang Chen (1 shared paper)Wangshu Liu (1 shared paper)Xingya Wang (1 shared paper)Qing Gu (1 shared paper)Cheng Li (1 shared paper)
- Journals
- Soft Computing (1 paper)Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (1 paper)Neurocomputing (1 paper)IEEE Sensors Journal (1 paper)View (2 papers)
- Partner nations
- ChinaUnited Kingdom
In The Last Decade
Shenkai Gu
8 papers receiving 372 citations
Peers
Comparison fields: 5 of 70
- Artificial Intelligence 293
- Computational Theory and Mathematics 80
- Computer Vision and Pattern Recognition 84
- Software 8
- Health Information Management 9
Countries citing papers authored by Shenkai Gu
This map shows the geographic impact of Shenkai Gu'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 Shenkai Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shenkai Gu more than expected).
Fields of papers citing papers by Shenkai Gu
This network shows the impact of papers produced by Shenkai Gu. 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 Shenkai Gu. The network helps show where Shenkai Gu may publish in the future.
Co-authors
The 13 scholars most cited alongside Shenkai Gu, 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 | 2016 | 274 | |
| 2 | 2017 | 32 | |
| 3 | 2015 | 28 | |
| 4 | 2014 | 28 | |
| 5 | 2022 | 6 | |
| 6 | 2012 | 6 | |
| 7 | 2021 | 3 | |
| 8 | 2022 | 3 |
About Shenkai Gu
Shenkai Gu is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computational Theory and Mathematics, Control and Systems Engineering and Information Systems, having authored 8 papers that have together received 380 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (3 papers), Machine Learning and Data Classification (2 papers), Anomaly Detection Techniques and Applications (2 papers), Advanced Multi-Objective Optimization Algorithms (2 papers), Evolutionary Algorithms and Applications (2 papers), Domain Adaptation and Few-Shot Learning (1 paper), Software System Performance and Reliability (1 paper) and Energy Efficient Wireless Sensor Networks (1 paper). The work is most often cited by research in Artificial Intelligence (293 citations), Computational Theory and Mathematics (80 citations), Computer Vision and Pattern Recognition (84 citations), Software (8 citations) and Health Information Management (9 citations). Shenkai Gu has collaborated with scholars based in China and United Kingdom. Frequent co-authors include Yaochu Jin, Ran Cheng, Li Cheng, Xiang Chen, Wangshu Liu, Xingya Wang, Qing Gu, Cheng Li, Yinghao Zheng and Xiaojian Yang. Their work appears in journals such as Soft Computing, Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, Neurocomputing, IEEE Sensors Journal and View.
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.