Peng Yao
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Oncology
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
- Topics
- Electrocatalysts for Energy Conversion (4 papers)Multimodal Machine Learning Applications (4 papers)AI in cancer detection (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceRenewable Energy, Sustainability and the Environment
- Journals
- SHILAP Revista de lepidopterologíaThe Journal of Physical Chemistry CNeuroscience
- Partner nations
- ChinaUnited StatesRussia
In The Last Decade
Peng Yao
18 papers receiving 552 citations
Peers
Comparison fields: 5 of 81
- Computer Vision and Pattern Recognition 287
- Artificial Intelligence 227
- Oncology 107
- Renewable Energy, Sustainability and the Environment 89
- Electrical and Electronic Engineering 67
Countries citing papers authored by Peng Yao
This map shows the geographic impact of Peng Yao'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 Peng Yao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peng Yao more than expected).
Fields of papers citing papers by Peng Yao
This network shows the impact of papers produced by Peng Yao. 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 Peng Yao. The network helps show where Peng Yao may publish in the future.
Co-authorship network of co-authors of Peng Yao
This figure shows the co-authorship network connecting the top 25 collaborators of Peng Yao. A scholar is included among the top collaborators of Peng Yao 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 Peng Yao. Peng Yao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 5 | |
| 3 | 0 | |
| 4 | 10 | |
| 5 | 8 | |
| 6 | 31 | |
| 7 | 41 | |
| 8 | 2 | |
| 9 | 35 | |
| 10 | 119 | |
| 11 | 15 | |
| 12 | 1 | |
| 13 | 171 | |
| 14 | 3 | |
| 15 | 16 | |
| 16 | 19 | |
| 17 | 69 | |
| 18 | 13 | |
| 19 | 2 |
About Peng Yao
Peng Yao is a scholar working on Computer Vision and Pattern Recognition, Renewable Energy, Sustainability and the Environment and Artificial Intelligence, having authored 19 papers that have together received 565 indexed citations. Recurring topics across this work include Electrocatalysts for Energy Conversion (4 papers), Multimodal Machine Learning Applications (4 papers) and AI in cancer detection (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (287 citations), Artificial Intelligence (227 citations) and Renewable Energy, Sustainability and the Environment (89 citations). Peng Yao has collaborated with scholars based in China, United States and Russia. Frequent co-authors include Longteng Guo, Jing Liu, Hanqing Lu, Xinxin Zhu, Shichen Lu, Shuwei Shen, Pengfei Shao, Ronald X. Xu, Peng Liu and Benjamin H. Kaffenberger. Their work appears in journals such as SHILAP Revista de lepidopterología, The Journal of Physical Chemistry C and Neuroscience.
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.