Jiawei Sheng
- Artificial Intelligence top 5%
- Information Systems top 10%
- Management Science and Operations Research top 10%
- Computer Vision and Pattern Recognition
- Computer Networks and Communications
- Co-authors
- Shu GuoTingwen LiuXin CongJiangxia CaoBin WangBowen YuYiming HeiHongbo Xü
- Topics
- Topic Modeling (24 papers)Natural Language Processing Techniques (15 papers)Advanced Graph Neural Networks (10 papers)
- Journals
- IEEE Transactions on Neural Networks and Learning SystemsNeurocomputingKnowledge-Based Systems
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Jiawei Sheng
23 papers receiving 310 citations
Peers
Comparison fields: 5 of 34
- Artificial Intelligence 282
- Information Systems 95
- Management Science and Operations Research 67
- Computer Vision and Pattern Recognition 51
- Computer Networks and Communications 10
Countries citing papers authored by Jiawei Sheng
This map shows the geographic impact of Jiawei Sheng'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 Jiawei Sheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiawei Sheng more than expected).
Fields of papers citing papers by Jiawei Sheng
This network shows the impact of papers produced by Jiawei Sheng. 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 Jiawei Sheng. The network helps show where Jiawei Sheng may publish in the future.
Co-authorship network of co-authors of Jiawei Sheng
This figure shows the co-authorship network connecting the top 25 collaborators of Jiawei Sheng. A scholar is included among the top collaborators of Jiawei Sheng 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 Jiawei Sheng. Jiawei Sheng 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 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 22 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 3 | |
| 11 | 8 | |
| 12 | 21 | |
| 13 | 7 | |
| 14 | 4 | |
| 15 | 31 | |
| 16 | Deep Learning Schema-based Event Extraction: Literature Review and Current Trends. | 2 |
| 17 | 8 | |
| 18 | 7 | |
| 19 | 6 | |
| 20 | 66 |
About Jiawei Sheng
Jiawei Sheng is a scholar working on Artificial Intelligence, Management Science and Operations Research and Information Systems, having authored 29 papers that have together received 318 indexed citations. Recurring topics across this work include Topic Modeling (24 papers), Natural Language Processing Techniques (15 papers) and Advanced Graph Neural Networks (10 papers). The work is most often cited by research in Artificial Intelligence (282 citations), Management Science and Operations Research (67 citations) and Information Systems (95 citations). Jiawei Sheng has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Shu Guo, Tingwen Liu, Tingwen Liu, Xin Cong, Jiangxia Cao, Bin Wang, Bowen Yu, Yiming Hei, Hongbo Xü and Qian Li. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Neurocomputing and Knowledge-Based Systems.
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.