Jingrui He
- Artificial Intelligence top 0.5%
- Computer Vision and Pattern Recognition top 1%
- Statistical and Nonlinear Physics top 2%
- Information Systems top 2%
- Computer Networks and Communications top 5%
- Topics
- Advanced Graph Neural Networks (32 papers)Domain Adaptation and Few-Shot Learning (28 papers)Complex Network Analysis Techniques (23 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionStatistical and Nonlinear Physics
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Jingrui He
149 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 139
- Artificial Intelligence 1.5k
- Computer Vision and Pattern Recognition 862
- Statistical and Nonlinear Physics 438
- Information Systems 324
- Computer Networks and Communications 201
Countries citing papers authored by Jingrui He
This map shows the geographic impact of Jingrui He'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 Jingrui He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jingrui He more than expected).
Fields of papers citing papers by Jingrui He
This network shows the impact of papers produced by Jingrui He. 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 Jingrui He. The network helps show where Jingrui He may publish in the future.
Co-authorship network of co-authors of Jingrui He
This figure shows the co-authorship network connecting the top 25 collaborators of Jingrui He. A scholar is included among the top collaborators of Jingrui He 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 Jingrui He. Jingrui He 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 | 1 | |
| 4 | 0 | |
| 5 | 8 | |
| 6 | 13 | |
| 7 | 0 | |
| 8 | 9 | |
| 9 | 5 | |
| 10 | 3 | |
| 11 | 10 | |
| 12 | 7 | |
| 13 | Crowdsourcing via tensor augmentation and completion | 24 |
| 14 | MUVIR: multi-view rare category detection | 21 |
| 15 | 26 | |
| 16 | Improving traffic prediction with tweet semantics | 64 |
| 17 | GenDeR: A Generic Diversified Ranking Algorithm | 12 |
| 18 | A Graph-based Framework for Multi-Task Multi-View Learning | 89 |
| 19 | 18 | |
| 20 | 34 |
About Jingrui He
Jingrui He is a scholar working on Computational Mathematics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 158 papers that have together received 2.5k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (32 papers), Domain Adaptation and Few-Shot Learning (28 papers) and Complex Network Analysis Techniques (23 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), Computer Vision and Pattern Recognition (862 citations) and Statistical and Nonlinear Physics (438 citations). Jingrui He has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Hanghang Tong, Dawei Zhou, Changshui Zhang, Mingjing Li, Hao Zhang, Jun Wu, Jaime Carbonell, Yada Zhu, Jiejun Xu and Richard D. Lawrence. Their work appears in journals such as Remote Sensing of Environment, Communications of the ACM and IEEE Access.
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.