Junzhou Huang
- Computer Vision and Pattern Recognition top 0.1%
- Artificial Intelligence top 0.1%
- Radiology, Nuclear Medicine and Imaging top 0.5%
- Molecular Biology top 5%
- Computational Mechanics top 0.5%
- Co-authors
- Yu RongWenbing HuangTingyang XuShaoting ZhangPeilin ZhaoDimitris MetaxasChen ChenTong Zhang
- Topics
- Sparse and Compressive Sensing Techniques (39 papers)AI in cancer detection (34 papers)Computational Drug Discovery Methods (31 papers)
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaBioinformatics
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Junzhou Huang
271 papers receiving 12.0k citations
Hit Papers
Peers
Comparison fields: 5 of 190
- Computer Vision and Pattern Recognition 5.4k
- Artificial Intelligence 5.2k
- Radiology, Nuclear Medicine and Imaging 2.1k
- Molecular Biology 1.3k
- Computational Mechanics 1.2k
Countries citing papers authored by Junzhou Huang
This map shows the geographic impact of Junzhou Huang'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 Junzhou Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junzhou Huang more than expected).
Fields of papers citing papers by Junzhou Huang
This network shows the impact of papers produced by Junzhou Huang. 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 Junzhou Huang. The network helps show where Junzhou Huang may publish in the future.
Co-authorship network of co-authors of Junzhou Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Junzhou Huang. A scholar is included among the top collaborators of Junzhou Huang 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 Junzhou Huang. Junzhou Huang 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 | 15 | |
| 4 | 7 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 11 | |
| 8 | 33 | |
| 9 | Not All Low-Pass Filters are Robust in Graph Convolutional Networks | 14 |
| 10 | 31 | |
| 11 | 14 | |
| 12 | 61 | |
| 13 | Adversarial Domain Adaptation for Cell Segmentation | 7 |
| 14 | 113 | |
| 15 | 21 | |
| 16 | Distributed Inexact Newton-type Pursuit for Non-convex Sparse Learning | 3 |
| 17 | Deep Multi-instance Learning with Dynamic Pooling | 19 |
| 18 | Multi-view matrix decomposition: a new scheme for exploring discriminative information | 23 |
| 19 | 4 | |
| 20 | 44 |
About Junzhou Huang
Junzhou Huang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 276 papers that have together received 12.2k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (39 papers), AI in cancer detection (34 papers) and Computational Drug Discovery Methods (31 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (5.4k citations), Artificial Intelligence (5.2k citations) and Computational Mathematics (67 citations). Junzhou Huang has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Yu Rong, Wenbing Huang, Tingyang Xu, Shaoting Zhang, Peilin Zhao, Dimitris Metaxas, Chen Chen, Tong Zhang, Dimitris Metaxas and Yeqing Li. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología 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.