Yun Luo
- Cognitive Neuroscience top 5%
- Artificial Intelligence top 5%
- Computer Networks and Communications top 5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Co-authors
- Bao‐Liang LuLianyong QiXiaolong XuShunmei MengXuyun ZhangKai PengQingxiang LiuYingying Jiao
- Topics
- EEG and Brain-Computer Interfaces (6 papers)Emotion and Mood Recognition (4 papers)Video Surveillance and Tracking Methods (4 papers)
- Cited by
- Cognitive NeuroscienceExperimental and Cognitive PsychologyComputer Networks and Communications
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Yun Luo
33 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 97
- Cognitive Neuroscience 314
- Artificial Intelligence 288
- Computer Networks and Communications 272
- Computer Vision and Pattern Recognition 188
- Information Systems 177
Countries citing papers authored by Yun Luo
This map shows the geographic impact of Yun Luo'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 Yun Luo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yun Luo more than expected).
Fields of papers citing papers by Yun Luo
This network shows the impact of papers produced by Yun Luo. 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 Yun Luo. The network helps show where Yun Luo may publish in the future.
Co-authorship network of co-authors of Yun Luo
This figure shows the co-authorship network connecting the top 25 collaborators of Yun Luo. A scholar is included among the top collaborators of Yun Luo 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 Yun Luo. Yun Luo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 111 | |
| 8 | 31 | |
| 9 | 192 | |
| 10 | 3 | |
| 11 | 113 | |
| 12 | 4 | |
| 13 | 5 | |
| 14 | 163 | |
| 15 | 43 | |
| 16 | 3 | |
| 17 | 43 | |
| 18 | 8 | |
| 19 | 3 | |
| 20 | Analysis on Influence of Locating Node Position of Tumbler Axle-box on Locomotive Dynamic Performance | 1 |
About Yun Luo
Yun Luo is a scholar working on Computational Mathematics, Experimental and Cognitive Psychology and Artificial Intelligence, having authored 35 papers that have together received 1.1k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (6 papers), Emotion and Mood Recognition (4 papers) and Video Surveillance and Tracking Methods (4 papers). The work is most often cited by research in Cognitive Neuroscience (314 citations), Experimental and Cognitive Psychology (174 citations) and Computer Networks and Communications (272 citations). Yun Luo has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Bao‐Liang Lu, Lianyong Qi, Xiaolong Xu, Shunmei Meng, Xuyun Zhang, Kai Peng, Qingxiang Liu, Yingying Jiao, Ziyu Wan and Anbu Huang. Their work appears in journals such as IEEE Access, IEEE Transactions on Industrial Informatics and Neurocomputing.
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.