Xiaolei Liu
- Artificial Intelligence top 5%
- Information Systems top 5%
- Computer Networks and Communications top 5%
- Signal Processing top 5%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Xiaosong ZhangTeng HuWeina NiuJiazhong LuQingxin ZhuTing ChenXiaojiang DuKun Zhou
- Topics
- Adversarial Robustness in Machine Learning (17 papers)Anomaly Detection Techniques and Applications (10 papers)Network Security and Intrusion Detection (9 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Xiaolei Liu
54 papers receiving 566 citations
Peers
Comparison fields: 5 of 76
- Artificial Intelligence 235
- Information Systems 220
- Computer Networks and Communications 172
- Signal Processing 134
- Computer Vision and Pattern Recognition 128
Countries citing papers authored by Xiaolei Liu
This map shows the geographic impact of Xiaolei Liu'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 Xiaolei Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaolei Liu more than expected).
Fields of papers citing papers by Xiaolei Liu
This network shows the impact of papers produced by Xiaolei Liu. 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 Xiaolei Liu. The network helps show where Xiaolei Liu may publish in the future.
Co-authorship network of co-authors of Xiaolei Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaolei Liu. A scholar is included among the top collaborators of Xiaolei Liu 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 Xiaolei Liu. Xiaolei Liu 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 | 0 | |
| 4 | 6 | |
| 5 | 7 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 2 | |
| 9 | 3 | |
| 10 | 0 | |
| 11 | 5 | |
| 12 | 5 | |
| 13 | 1 | |
| 14 | 3 | |
| 15 | 3 | |
| 16 | 153 | |
| 17 | 2 | |
| 18 | 9 | |
| 19 | Fault diagnosis of elevator control system based on information fusion | 1 |
| 20 | PID Control Algorithm Based on Improved BP Neural Network | 1 |
About Xiaolei Liu
Xiaolei Liu is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 63 papers that have together received 595 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (17 papers), Anomaly Detection Techniques and Applications (10 papers) and Network Security and Intrusion Detection (9 papers). The work is most often cited by research in Signal Processing (134 citations), Information Systems (220 citations) and Computer Networks and Communications (172 citations). Xiaolei Liu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xiaosong Zhang, Teng Hu, Weina Niu, Jiazhong Lu, Qingxin Zhu, Ting Chen, Xiaojiang Du, Kun Zhou, Xiaoming Huang and Mohsen Guizani. Their work appears in journals such as Chemical Engineering Journal, Sensors and IEEE Transactions on Intelligent Transportation 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.