Bo Pang
- Artificial Intelligence top 10%
- Information Systems top 5%
- Complementary and alternative medicine top 5%
- Computer Vision and Pattern Recognition top 10%
- Sociology and Political Science
- Co-authors
- Lillian LeeJon KleinbergCristian Danescu-Niculescu-MizilYuanchao LiuDavid ZhangXiaolong WangTao LiuKuanquan Wang
- Topics
- Traditional Chinese Medicine Studies (3 papers)Advanced Vision and Imaging (3 papers)Spam and Phishing Detection (2 papers)
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsComposites Part A Applied Science and Manufacturing
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Bo Pang
27 papers receiving 578 citations
Peers
Comparison fields: 5 of 114
- Artificial Intelligence 184
- Information Systems 107
- Complementary and alternative medicine 96
- Computer Vision and Pattern Recognition 91
- Sociology and Political Science 72
Countries citing papers authored by Bo Pang
This map shows the geographic impact of Bo Pang'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 Pang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bo Pang more than expected).
Fields of papers citing papers by Bo Pang
This network shows the impact of papers produced by Bo Pang. 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 Pang. The network helps show where Bo Pang may publish in the future.
Co-authorship network of co-authors of Bo Pang
This figure shows the co-authorship network connecting the top 25 collaborators of Bo Pang. A scholar is included among the top collaborators of Bo Pang 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 Bo Pang. Bo Pang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 8 | |
| 9 | 54 | |
| 10 | 6 | |
| 11 | 59 | |
| 12 | 8 | |
| 13 | 1 | |
| 14 | 48 | |
| 15 | 4 | |
| 16 | 4 | |
| 17 | 178 | |
| 18 | 0 | |
| 19 | 1 | |
| 20 | 46 |
About Bo Pang
Bo Pang is a scholar working on Complementary and alternative medicine, Computer Vision and Pattern Recognition and Statistics, Probability and Uncertainty, having authored 29 papers that have together received 603 indexed citations. Recurring topics across this work include Traditional Chinese Medicine Studies (3 papers), Advanced Vision and Imaging (3 papers) and Spam and Phishing Detection (2 papers). The work is most often cited by research in Complementary and alternative medicine (96 citations), Artificial Intelligence (184 citations) and Language and Linguistics (54 citations). Bo Pang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Lillian Lee, Jon Kleinberg, Cristian Danescu-Niculescu-Mizil, Yuanchao Liu, David Zhang, Xiaolong Wang, Tao Liu, Kuanquan Wang, Bo Huang and Chuanhui Gao. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Composites Part A Applied Science and Manufacturing.
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.