Wangchunshu Zhou
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems
- Sociology and Political Science
- Signal Processing
- Topics
- Topic Modeling (26 papers)Natural Language Processing Techniques (20 papers)Multimodal Machine Learning Applications (11 papers)
- Journals
- Nature CommunicationsIEEE Transactions on Pattern Analysis and Machine IntelligenceEngineering Applications of Artificial Intelligence
- Partner nations
- ChinaUnited StatesSwitzerland
In The Last Decade
Wangchunshu Zhou
34 papers receiving 458 citations
Peers
Comparison fields: 5 of 57
- Artificial Intelligence 382
- Computer Vision and Pattern Recognition 174
- Information Systems 29
- Sociology and Political Science 18
- Signal Processing 16
Countries citing papers authored by Wangchunshu Zhou
This map shows the geographic impact of Wangchunshu Zhou'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 Wangchunshu Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wangchunshu Zhou more than expected).
Fields of papers citing papers by Wangchunshu Zhou
This network shows the impact of papers produced by Wangchunshu Zhou. 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 Wangchunshu Zhou. The network helps show where Wangchunshu Zhou may publish in the future.
Co-authorship network of co-authors of Wangchunshu Zhou
This figure shows the co-authorship network connecting the top 25 collaborators of Wangchunshu Zhou. A scholar is included among the top collaborators of Wangchunshu Zhou 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 Wangchunshu Zhou. Wangchunshu Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 2 | |
| 3 | 22 | |
| 4 | 12 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 14 | |
| 8 | 32 | |
| 9 | 2 | |
| 10 | 2 | |
| 11 | 4 | |
| 12 | 3 | |
| 13 | 1 | |
| 14 | 36 | |
| 15 | 1 | |
| 16 | Pre-training Text-to-Text Transformers for Concept-centric Common Sense | 30 |
| 17 | 22 | |
| 18 | 100 | |
| 19 | Towards Interpretable Natural Language Understanding with Explanations as Latent Variables | 1 |
| 20 | 48 |
About Wangchunshu Zhou
Wangchunshu Zhou is a scholar working on Artificial Intelligence, Health Informatics and Computer Vision and Pattern Recognition, having authored 37 papers that have together received 476 indexed citations. Recurring topics across this work include Topic Modeling (26 papers), Natural Language Processing Techniques (20 papers) and Multimodal Machine Learning Applications (11 papers). The work is most often cited by research in Artificial Intelligence (382 citations), Computer Vision and Pattern Recognition (174 citations) and Health Informatics (5 citations). Wangchunshu Zhou has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Tao Ge, Furu Wei, Canwen Xu, Ming Zhou, Ke Xu, Julian McAuley, Ke Xu, Ming Zhou, Xinsong Zhang and Siyu Lu. Their work appears in journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence and Engineering Applications of Artificial Intelligence.
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.