Jun Huan
Impact in
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- Graph Theory and Algorithms
- Signal Processing top 2%
- Data Management and Algorithms
Papers in
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- Domain Adaptation and Few-Shot Learning 21
- Machine Learning and ELM 8
- Machine Learning and Data Classification 6
- Machine Learning and Algorithms 6
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- Graph Theory and Algorithms 7
- Multimodal Machine Learning Applications 6
- Advanced Neural Network Applications 6
- Co-authors
- Wei Wang (8 shared papers)Jan F. Prins (6 shared papers)Brian Quanz (3 shared papers)Jiong Yang (1 shared paper)Jintao Zhang (1 shared paper)Haoyi Xiong (15 shared papers)Tianyang Wang (4 shared papers)Jack Scott Snoeyink (7 shared papers)
- Journals
- ACM Transactions on Knowledge Discovery from Data (5 papers)IEEE Transactions on Knowledge and Data Engineering (3 papers)ACM Transactions on Intelligent Systems and Technology (2 papers)IEEE Transactions on Neural Networks and Learning Systems (1 paper)IEEE Transactions on Computational Biology and Bioinformatics (1 paper)
- Partner nations
- United StatesChinaMacao
In The Last Decade
Jun Huan
54 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 105
- Computer Vision and Pattern Recognition 662
- Signal Processing 324
- Information Systems 509
- Artificial Intelligence 736
- Computational Theory and Mathematics 191
Countries citing papers authored by Jun Huan
This map shows the geographic impact of Jun Huan'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 Jun Huan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Huan more than expected).
Fields of papers citing papers by Jun Huan
This network shows the impact of papers produced by Jun Huan. 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 Jun Huan. The network helps show where Jun Huan may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Huan, 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 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 444 | |
| 2 | 2004 | 251 | |
| 3 | 2009 | 113 | |
| 4 | 2012 | 110 | |
| 5 | 2004 | 84 | |
| 6 | 2020 | 53 | |
| 7 | 2021 | 52 | |
| 8 | 2012 | 52 | |
| 9 | 2019 | 36 | |
| 10 | 2019 | 34 | |
| 11 | 2018 | 29 | |
| 12 | 2018 | 28 | |
| 13 | 2006 | 24 | |
| 14 | 2020 | 22 | |
| 15 | 2015 | 20 | |
| 16 | 2011 | 19 | |
| 17 | 2011 | 18 | |
| 18 | 2021 | 17 | |
| 19 | 2022 | 16 | |
| 20 | 2020 | 14 |
About Jun Huan
Jun Huan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics, Signal Processing and Statistics and Probability, having authored 56 papers that have together received 1.6k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (21 papers), Machine Learning and ELM (8 papers), Graph Theory and Algorithms (7 papers), Multimodal Machine Learning Applications (6 papers), Advanced Neural Network Applications (6 papers), Machine Learning and Data Classification (6 papers), Machine Learning and Algorithms (6 papers) and Sparse and Compressive Sensing Techniques (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (662 citations), Signal Processing (324 citations), Information Systems (509 citations), Artificial Intelligence (736 citations) and Computational Theory and Mathematics (191 citations). Jun Huan has collaborated with scholars based in United States, China and Macao. Frequent co-authors include Wei Wang, Jan F. Prins, Brian Quanz, Jiong Yang, Jintao Zhang, Haoyi Xiong, Tianyang Wang, Jack Scott Snoeyink, Deepak Bandyopadhyay and Alexander Tropsha. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Intelligent Systems and Technology, IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Computational Biology and Bioinformatics.
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.