Xiaokang Zhou
- Artificial Intelligence top 0.2%
- Computer Networks and Communications top 0.5%
- Information Systems top 0.2%
- Computer Vision and Pattern Recognition top 1%
- Electrical and Electronic Engineering top 5%
- Topics
- IoT and Edge/Fog Computing (29 papers)Privacy-Preserving Technologies in Data (29 papers)Recommender Systems and Techniques (26 papers)
- Journals
- Expert Systems with ApplicationsIEEE AccessIEEE Journal on Selected Areas in Communications
- Partner nations
- JapanChinaNew Zealand
In The Last Decade
Xiaokang Zhou
190 papers receiving 6.7k citations
Hit Papers
Peers
Comparison fields: 5 of 175
- Artificial Intelligence 2.9k
- Computer Networks and Communications 2.2k
- Information Systems 1.6k
- Computer Vision and Pattern Recognition 1.1k
- Electrical and Electronic Engineering 1.0k
Countries citing papers authored by Xiaokang Zhou
This map shows the geographic impact of Xiaokang Zhou'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 Xiaokang Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaokang Zhou more than expected).
Fields of papers citing papers by Xiaokang Zhou
This network shows the impact of papers produced by Xiaokang Zhou. 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 Xiaokang Zhou. The network helps show where Xiaokang Zhou may publish in the future.
Co-authorship network of co-authors of Xiaokang Zhou
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaokang Zhou. A scholar is included among the top collaborators of Xiaokang Zhou 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 Xiaokang Zhou. Xiaokang Zhou 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 | 0 | |
| 3 | 8 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 21 | |
| 7 | 23 | |
| 8 | 71 | |
| 9 | Digital Twin Enhanced Federated Reinforcement Learning With Lightweight Knowledge Distillation in Mobile Networksbreakdown → | 119 |
| 10 | 28 | |
| 11 | 58 | |
| 12 | 32 | |
| 13 | 124 | |
| 14 | 45 | |
| 15 | 3 | |
| 16 | 96 | |
| 17 | Intelligent Small Object Detection for Digital Twin in Smart Manufacturing With Industrial Cyber-Physical Systemsbreakdown → | 212 |
| 18 | Variational LSTM Enhanced Anomaly Detection for Industrial Big Databreakdown → | 290 |
| 19 | Siamese Neural Network Based Few-Shot Learning for Anomaly Detection in Industrial Cyber-Physical Systemsbreakdown → | 248 |
| 20 | 44 |
About Xiaokang Zhou
Xiaokang Zhou is a scholar working on Computational Mathematics, Computer Networks and Communications and Artificial Intelligence, having authored 214 papers that have together received 6.9k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (29 papers), Privacy-Preserving Technologies in Data (29 papers) and Recommender Systems and Techniques (26 papers). The work is most often cited by research in Computer Networks and Communications (2.2k citations), Artificial Intelligence (2.9k citations) and Information Systems (1.6k citations). Xiaokang Zhou has collaborated with scholars based in Japan, China and New Zealand. Frequent co-authors include Wei Liang, Kevin I‐Kai Wang, Qun Jin, Jianhua Ma, Zheng Yan, Shohei Shimizu, Laurence T. Yang, Ke Yan, Yue Li and Xiaolong Xu. Their work appears in journals such as Expert Systems with Applications, IEEE Access and IEEE Journal on Selected Areas in Communications.
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.