Junzhou Zhao
- Artificial Intelligence top 5%
- Statistical and Nonlinear Physics top 5%
- Computer Networks and Communications top 10%
- Information Systems top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Pinghui WangJohn C. S. LuiXiaohong GuanDon TowsleyJing TaoLong ChenXiaoyan WangLi Pan
- Topics
- Complex Network Analysis Techniques (27 papers)Advanced Graph Neural Networks (16 papers)Opinion Dynamics and Social Influence (7 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInformation SciencesIEEE Transactions on Knowledge and Data Engineering
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Junzhou Zhao
57 papers receiving 615 citations
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 315
- Statistical and Nonlinear Physics 220
- Computer Networks and Communications 115
- Information Systems 92
- Computer Vision and Pattern Recognition 87
Countries citing papers authored by Junzhou Zhao
This map shows the geographic impact of Junzhou Zhao'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 Junzhou Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junzhou Zhao more than expected).
Fields of papers citing papers by Junzhou Zhao
This network shows the impact of papers produced by Junzhou Zhao. 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 Junzhou Zhao. The network helps show where Junzhou Zhao may publish in the future.
Co-authorship network of co-authors of Junzhou Zhao
This figure shows the co-authorship network connecting the top 25 collaborators of Junzhou Zhao. A scholar is included among the top collaborators of Junzhou Zhao 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 Junzhou Zhao. Junzhou Zhao 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 | 1 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 8 | |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 3 | |
| 10 | 1 | |
| 11 | 0 | |
| 12 | 0 | |
| 13 | 88 | |
| 14 | 1 | |
| 15 | 38 | |
| 16 | 13 | |
| 17 | Efficiently Estimating Subgraph Statistics of Large Networks in the Dark. | 1 |
| 18 | 5 | |
| 19 | 1 | |
| 20 | 25 |
About Junzhou Zhao
Junzhou Zhao is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Computer Networks and Communications, having authored 62 papers that have together received 620 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (27 papers), Advanced Graph Neural Networks (16 papers) and Opinion Dynamics and Social Influence (7 papers). The work is most often cited by research in Statistical and Nonlinear Physics (220 citations), Artificial Intelligence (315 citations) and Transportation (39 citations). Junzhou Zhao has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Pinghui Wang, John C. S. Lui, Xiaohong Guan, Don Towsley, Jing Tao, Long Chen, Xiaoyan Wang, Li Pan, Bruno Ribeiro and Xiangliang Zhang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Information Sciences and IEEE Transactions on Knowledge and Data Engineering.
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.