Weiqi Luo
- Artificial Intelligence top 5%
- Computer Networks and Communications top 10%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Signal Processing top 10%
- Co-authors
- Jian WengXizhao LuoAnjia YangZitao LiuGuo‐Qiang ZengQuanlong GuanXin ChenQi Tian
- Topics
- Privacy-Preserving Technologies in Data (11 papers)Topic Modeling (9 papers)Intelligent Tutoring Systems and Adaptive Learning (9 papers)
In The Last Decade
Weiqi Luo
56 papers receiving 646 citations
Peers
Comparison fields: 5 of 79
- Artificial Intelligence 378
- Computer Networks and Communications 150
- Information Systems 125
- Computer Vision and Pattern Recognition 124
- Signal Processing 91
Countries citing papers authored by Weiqi Luo
This map shows the geographic impact of Weiqi 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 Weiqi Luo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weiqi Luo more than expected).
Fields of papers citing papers by Weiqi Luo
This network shows the impact of papers produced by Weiqi 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 Weiqi Luo. The network helps show where Weiqi Luo may publish in the future.
Co-authorship network of co-authors of Weiqi Luo
This figure shows the co-authorship network connecting the top 25 collaborators of Weiqi Luo. A scholar is included among the top collaborators of Weiqi 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 Weiqi Luo. Weiqi 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 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 11 | |
| 9 | 15 | |
| 10 | 15 | |
| 11 | 1 | |
| 12 | 19 | |
| 13 | 3 | |
| 14 | 2 | |
| 15 | 77 | |
| 16 | 0 | |
| 17 | The risk infection for the bank of met population model——Based on the dynamic simulation of the cellular automata | 1 |
| 18 | Design and Implementation of NAC Model Based on 802.1x | 1 |
| 19 | Personalized recommend system based on peer to peer network | 2 |
| 20 | Design of the CORBA-based Distributed Workflow Management System | 0 |
About Weiqi Luo
Weiqi Luo is a scholar working on Computer Science Applications, Artificial Intelligence and Human-Computer Interaction, having authored 63 papers that have together received 661 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (11 papers), Topic Modeling (9 papers) and Intelligent Tutoring Systems and Adaptive Learning (9 papers). The work is most often cited by research in Artificial Intelligence (378 citations), Computer Science Applications (54 citations) and Signal Processing (91 citations). Weiqi Luo has collaborated with scholars based in China, Australia and Canada. Frequent co-authors include Jian Weng, Xizhao Luo, Anjia Yang, Zitao Liu, Guo‐Qiang Zeng, Quanlong Guan, Xin Chen, Qi Tian, Yongdong Wu and Kang‐Di Lu. Their work appears in journals such as Physical Review Letters, Scientific Reports and IEEE Transactions on Information Theory.
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.