Zhuoren Jiang
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 10%
- Media Technology top 10%
- Computational Theory and Mathematics top 10%
- Topics
- Topic Modeling (22 papers)Advanced Text Analysis Techniques (10 papers)Advanced Graph Neural Networks (8 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionComputer Science Applications
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Zhuoren Jiang
49 papers receiving 491 citations
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 302
- Computer Vision and Pattern Recognition 189
- Information Systems 98
- Media Technology 45
- Computational Theory and Mathematics 42
Countries citing papers authored by Zhuoren Jiang
This map shows the geographic impact of Zhuoren Jiang'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 Zhuoren Jiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhuoren Jiang more than expected).
Fields of papers citing papers by Zhuoren Jiang
This network shows the impact of papers produced by Zhuoren Jiang. 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 Zhuoren Jiang. The network helps show where Zhuoren Jiang may publish in the future.
Co-authorship network of co-authors of Zhuoren Jiang
This figure shows the co-authorship network connecting the top 25 collaborators of Zhuoren Jiang. A scholar is included among the top collaborators of Zhuoren Jiang 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 Zhuoren Jiang. Zhuoren Jiang 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 | 3 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 7 | |
| 9 | 4 | |
| 10 | 3 | |
| 11 | 6 | |
| 12 | 4 | |
| 13 | An End-to-end Model of Predicting Diverse Ranking On Heterogeneous Feeds. | 2 |
| 14 | 20 | |
| 15 | 62 | |
| 16 | 1 | |
| 17 | The Math Retrieval System of ICST for NTCIR-12 MathIR Task. | 7 |
| 18 | Random Walk and Feedback on Scholarly Network. | 0 |
| 19 | 2 | |
| 20 | Citation Recommendation via Time-series Scholarly Topic Analysis and Publication Prior Analysis. | 1 |
About Zhuoren Jiang
Zhuoren Jiang is a scholar working on Artificial Intelligence, Computer Science Applications and Information Systems, having authored 56 papers that have together received 521 indexed citations. Recurring topics across this work include Topic Modeling (22 papers), Advanced Text Analysis Techniques (10 papers) and Advanced Graph Neural Networks (8 papers). The work is most often cited by research in Artificial Intelligence (302 citations), Computer Vision and Pattern Recognition (189 citations) and Computer Science Applications (28 citations). Zhuoren Jiang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Liangcai Gao, Xiaozhong Liu, Zhi Tang, Xiaohan Yi, Yangyang Kang, Changlong Sun, Yao Lu, Yuan Liao, Yao Lu and Runtao Liu. Their work appears in journals such as Scientometrics, Neural Computing and Applications and Information Processing & Management.
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.