Yixin Cao
- Artificial Intelligence top 2%
- Information Systems top 2%
- Computer Vision and Pattern Recognition top 5%
- Management Science and Operations Research top 5%
- Water Science and Technology top 10%
- Topics
- Topic Modeling (30 papers)Natural Language Processing Techniques (24 papers)Advanced Graph Neural Networks (9 papers)
- Journals
- Chemical Engineering JournalInternational Journal of Molecular SciencesIEEE Transactions on Knowledge and Data Engineering
- Partner nations
- ChinaSingaporeUnited States
In The Last Decade
Yixin Cao
39 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 85
- Artificial Intelligence 755
- Information Systems 353
- Computer Vision and Pattern Recognition 258
- Management Science and Operations Research 175
- Water Science and Technology 75
Countries citing papers authored by Yixin Cao
This map shows the geographic impact of Yixin Cao'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 Yixin Cao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yixin Cao more than expected).
Fields of papers citing papers by Yixin Cao
This network shows the impact of papers produced by Yixin Cao. 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 Yixin Cao. The network helps show where Yixin Cao may publish in the future.
Co-authorship network of co-authors of Yixin Cao
This figure shows the co-authorship network connecting the top 25 collaborators of Yixin Cao. A scholar is included among the top collaborators of Yixin Cao 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 Yixin Cao. Yixin Cao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 4 | |
| 8 | 2 | |
| 9 | 14 | |
| 10 | 8 | |
| 11 | 6 | |
| 12 | 16 | |
| 13 | 1 | |
| 14 | 4 | |
| 15 | 67 | |
| 16 | 30 | |
| 17 | 74 | |
| 18 | Neural Collective Entity Linking | 21 |
| 19 | 25 | |
| 20 | On Modeling Sense Relatedness in Multi-prototype Word Embedding | 1 |
About Yixin Cao
Yixin Cao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Management Science and Operations Research, having authored 46 papers that have together received 1.1k indexed citations. Recurring topics across this work include Topic Modeling (30 papers), Natural Language Processing Techniques (24 papers) and Advanced Graph Neural Networks (9 papers). The work is most often cited by research in Artificial Intelligence (755 citations), Information Systems (353 citations) and Management Science and Operations Research (175 citations). Yixin Cao has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Zheng Qin, Hongyuan Zha, Hongteng Xu, Yongfeng Zhang, Jiaxi Tang, Xu Chen, Juanzi Li, Tat‐Seng Chua, Lei Hou and Xingzhong Yuan. Their work appears in journals such as Chemical Engineering Journal, International Journal of Molecular 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.