Jun Ni
Impact in
- Artificial Intelligence top 5%
- Imbalanced Data Classification Techniques
- Machine Learning and Data Classification
- Anomaly Detection Techniques and Applications
Papers in
-
- Distributed and Parallel Computing Systems 9
- Co-authors
- Hualong Yu (5 shared papers)Jing Zhao (1 shared paper)Ge Wang (9 shared papers)Chun-Hsi Huang (1 shared paper)Shaowen Wang (5 shared papers)Bin Qin (2 shared papers)Xiang Li (1 shared paper)Marc P. Armstrong (1 shared paper)
- Journals
- BMC Bioinformatics (5 papers)Neurocomputing (1 paper)IEEE/ACM Transactions on Computational Biology and Bioinformatics (1 paper)BioMed Research International (1 paper)Journal of Manufacturing Science and Engineering (1 paper)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Jun Ni
51 papers receiving 550 citations
Peers
Comparison fields: 5 of 113
- Artificial Intelligence 292
- Health Information Management 33
- Information Systems and Management 29
- Media Technology 27
- Health Informatics 4
Countries citing papers authored by Jun Ni
This map shows the geographic impact of Jun Ni'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 Ni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Ni more than expected).
Fields of papers citing papers by Jun Ni
This network shows the impact of papers produced by Jun Ni. 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 Ni. The network helps show where Jun Ni may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Ni, 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 57 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 156 | |
| 2 | 2014 | 81 | |
| 3 | 2013 | 34 | |
| 4 | 2006 | 30 | |
| 5 | 2005 | 25 | |
| 6 | Proceedings of The 2005 International Conference on Internet Computing, ICOMP 2005 | 2007 | 24 |
| 7 | 2009 | 23 | |
| 8 | 2005 | 20 | |
| 9 | 2006 | 19 | |
| 10 | 2008 | 15 | |
| 11 | 2013 | 13 | |
| 12 | 1998 | 12 | |
| 13 | 2014 | 12 | |
| 14 | 2006 | 12 | |
| 15 | 2008 | 9 | |
| 16 | 2009 | 9 | |
| 17 | 2010 | 7 | |
| 18 | 2008 | 7 | |
| 19 | 2007 | 7 | |
| 20 | 2008 | 7 |
About Jun Ni
Jun Ni is a scholar working on Computer Networks and Communications, Information Systems, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 57 papers that have together received 594 indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (9 papers), Distributed and Parallel Computing Systems (9 papers), Advanced X-ray and CT Imaging (7 papers), Gene expression and cancer classification (6 papers), Imbalanced Data Classification Techniques (4 papers), Data Management and Algorithms (3 papers), Digital Radiography and Breast Imaging (3 papers) and Advanced MRI Techniques and Applications (3 papers). The work is most often cited by research in Artificial Intelligence (292 citations), Health Information Management (33 citations), Information Systems and Management (29 citations), Media Technology (27 citations) and Health Informatics (4 citations). Jun Ni has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Hualong Yu, Jing Zhao, Ge Wang, Chun-Hsi Huang, Shaowen Wang, Bin Qin, Xiang Li, Marc P. Armstrong, Yan Liu and Xibei Yang. Their work appears in journals such as BMC Bioinformatics, Neurocomputing, IEEE/ACM Transactions on Computational Biology and Bioinformatics, BioMed Research International and Journal of Manufacturing Science and 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.