Bo-Lun Chen
Impact in
-
- Complex Network Analysis Techniques
-
- Physics of Superconductivity and Magnetism
Papers in
-
- Complex Network Analysis Techniques 9
- Opinion Dynamics and Social Influence 4
-
- Advanced Graph Neural Networks 4
- Co-authors
- Jingjing Wan (8 shared papers)Yongtao Yu (7 shared papers)Su-Peng Kou (4 shared papers)Yunbo Zhang (2 shared papers)Xiaobin Huang (1 shared paper)Shu Chen (1 shared paper)Ying Jin (1 shared paper)Claudio J. Tessone (2 shared papers)
- Journals
- Scientific Reports (5 papers)IEEE Access (2 papers)Physics Letters A (2 papers)Physical Review A (2 papers)Computers, materials & continua/Computers, materials & continua (Print) (2 papers)
- Partner nations
- ChinaSwitzerlandTaiwan
In The Last Decade
Bo-Lun Chen
30 papers receiving 336 citations
Peers
Comparison fields: 5 of 87
- Statistical and Nonlinear Physics 55
- Condensed Matter Physics 41
- Radiology, Nuclear Medicine and Imaging 70
- Oncology 71
- Computer Vision and Pattern Recognition 52
Countries citing papers authored by Bo-Lun Chen
This map shows the geographic impact of Bo-Lun Chen'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 Bo-Lun Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bo-Lun Chen more than expected).
Fields of papers citing papers by Bo-Lun Chen
This network shows the impact of papers produced by Bo-Lun Chen. 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 Bo-Lun Chen. The network helps show where Bo-Lun Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Bo-Lun Chen, 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 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 67 | |
| 2 | 2008 | 38 | |
| 3 | 2021 | 33 | |
| 4 | 2010 | 30 | |
| 5 | 2019 | 28 | |
| 6 | 2022 | 21 | |
| 7 | 2018 | 19 | |
| 8 | 2022 | 13 | |
| 9 | 2023 | 11 | |
| 10 | 2006 | 10 | |
| 11 | 2018 | 8 | |
| 12 | 2024 | 7 | |
| 13 | 2024 | 6 | |
| 14 | 2023 | 5 | |
| 15 | 2024 | 5 | |
| 16 | 2024 | 4 | |
| 17 | 2024 | 4 | |
| 18 | 2020 | 4 | |
| 19 | 2015 | 4 | |
| 20 | 2024 | 3 |
About Bo-Lun Chen
Bo-Lun Chen is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Computer Vision and Pattern Recognition, Oncology and Radiology, Nuclear Medicine and Imaging, having authored 35 papers that have together received 344 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (9 papers), Colorectal Cancer Screening and Detection (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Advanced Graph Neural Networks (4 papers), Advanced Neural Network Applications (4 papers), Opinion Dynamics and Social Influence (4 papers), Cold Atom Physics and Bose-Einstein Condensates (3 papers) and Recommender Systems and Techniques (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (55 citations), Condensed Matter Physics (41 citations), Radiology, Nuclear Medicine and Imaging (70 citations), Oncology (71 citations) and Computer Vision and Pattern Recognition (52 citations). Bo-Lun Chen has collaborated with scholars based in China, Switzerland and Taiwan. Frequent co-authors include Jingjing Wan, Yongtao Yu, Su-Peng Kou, Yunbo Zhang, Xiaobin Huang, Shu Chen, Ying Jin, Claudio J. Tessone, Jianhong Lin and Wenxin Jiang. Their work appears in journals such as Scientific Reports, IEEE Access, Physics Letters A, Physical Review A and Computers, materials & continua/Computers, materials & continua (Print).
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.