Chaobo He
Impact in
- Computational Mathematics top 10%
-
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
Papers in
-
- Complex Network Analysis Techniques 31
-
- Advanced Graph Neural Networks 33
- Text and Document Classification Technologies 9
- Topic Modeling 5
- Co-authors
- Yong Tang (32 shared papers)Xiang Fei (19 shared papers)Hanchao Li (17 shared papers)Dong Huang (2 shared papers)Wang Chang-dong (2 shared papers)Zeng Hu (3 shared papers)Junwei Cheng (15 shared papers)Shuangyin Liu (6 shared papers)
- Journals
- Neural Networks (2 papers)Physica A Statistical Mechanics and its Applications (2 papers)IEEE Access (2 papers)Neurocomputing (2 papers)Journal of Ambient Intelligence and Humanized Computing (1 paper)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Chaobo He
61 papers receiving 637 citations
Chaobo He's Hit Papers
Peers
Comparison fields: 5 of 70
- Computational Mathematics 13
- Statistical and Nonlinear Physics 259
- Artificial Intelligence 362
- Computer Vision and Pattern Recognition 186
- Urban Studies 41
Countries citing papers authored by Chaobo He
This map shows the geographic impact of Chaobo 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 Chaobo He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chaobo He more than expected).
Fields of papers citing papers by Chaobo He
This network shows the impact of papers produced by Chaobo 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 Chaobo He. The network helps show where Chaobo He may publish in the future.
Co-authors
The 25 scholars most cited alongside Chaobo He, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Efficient Multi-View Clustering via Unified and Discrete Bipartite Graph Learning Hit paper breakdown → | 2023 | 142 |
| 2 | 2021 | 93 | |
| 3 | 2022 | 44 | |
| 4 | 2021 | 43 | |
| 5 | 1986 | 28 | |
| 6 | 2023 | 19 | |
| 7 | 2018 | 18 | |
| 8 | 2020 | 14 | |
| 9 | 2018 | 13 | |
| 10 | 2024 | 13 | |
| 11 | 2018 | 12 | |
| 12 | 2019 | 12 | |
| 13 | 2024 | 12 | |
| 14 | 2016 | 11 | |
| 15 | 2020 | 11 | |
| 16 | 2023 | 11 | |
| 17 | 2015 | 9 | |
| 18 | 2019 | 9 | |
| 19 | 2014 | 8 | |
| 20 | 2023 | 8 |
About Chaobo He
Chaobo He is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Information Systems, Signal Processing and Computer Vision and Pattern Recognition, having authored 72 papers that have together received 653 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (33 papers), Complex Network Analysis Techniques (31 papers), Recommender Systems and Techniques (16 papers), Text and Document Classification Technologies (9 papers), Music and Audio Processing (7 papers), Music Technology and Sound Studies (5 papers), Topic Modeling (5 papers) and Advanced Computing and Algorithms (5 papers). The work is most often cited by research in Computational Mathematics (13 citations), Statistical and Nonlinear Physics (259 citations), Artificial Intelligence (362 citations), Computer Vision and Pattern Recognition (186 citations) and Urban Studies (41 citations). Chaobo He has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Yong Tang, Xiang Fei, Hanchao Li, Dong Huang, Wang Chang-dong, Zeng Hu, Junwei Cheng, Shuangyin Liu, Miranda Lee Pao and Quanlong Guan. Their work appears in journals such as Neural Networks, Physica A Statistical Mechanics and its Applications, IEEE Access, Neurocomputing and Journal of Ambient Intelligence and Humanized Computing.
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.