Xiaonan Yang
- Sensory Systems top 10%
- Biophysics top 10%
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- Microfluidic and Bio-sensing Technologies 8
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- Semiconductor materials and devices 13
- Advanced Memory and Neural Computing 8
- Advanced Fiber Optic Sensors 7
- Advancements in Semiconductor Devices and Circuit Design 6
- Photonic and Optical Devices 5
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- Manufacturing Process and Optimization 5
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- Digital Imaging for Blood Diseases 4
- Co-authors
- Yongjun WuLihua DingJianhua MiaoKunhua WeiSun Chul KangImran KhanLing KuiWei Chen
- Journals
- IEEE Electron Device Letters (4 papers)Biosensors and Bioelectronics (4 papers)Analytical and Bioanalytical Chemistry (3 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Xiaonan Yang
96 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 141
- Cancer Research 127
- Sensory Systems 31
- Molecular Biology 412
- Biophysics 34
- Biomedical Engineering 242
Countries citing papers authored by Xiaonan Yang
This map shows the geographic impact of Xiaonan Yang'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 Xiaonan Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaonan Yang more than expected).
Fields of papers citing papers by Xiaonan Yang
This network shows the impact of papers produced by Xiaonan Yang. 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 Xiaonan Yang. The network helps show where Xiaonan Yang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiaonan Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 6 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2025 | 0 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 3 | |
| 8 | 2024 | 5 | |
| 9 | 2024 | 9 | |
| 10 | 2024 | 1 | |
| 11 | 2024 | 4 | |
| 12 | 2024 | 6 | |
| 13 | 2023 | 6 | |
| 14 | 2023 | 7 | |
| 15 | 2022 | 4 | |
| 16 | 2022 | 46 | |
| 17 | 2022 | 6 | |
| 18 | 2021 | 18 | |
| 19 | 2021 | 8 | |
| 20 | 2021 | 2 |
About Xiaonan Yang
Xiaonan Yang is a scholar working on Industrial and Manufacturing Engineering, Biophysics and Computer Vision and Pattern Recognition, having authored 111 papers that have together received 1.1k indexed citations. Recurring topics across this work include Semiconductor materials and devices (13 papers), Advanced Memory and Neural Computing (8 papers), Microfluidic and Bio-sensing Technologies (8 papers), Advanced Fiber Optic Sensors (7 papers), Advancements in Semiconductor Devices and Circuit Design (6 papers), Manufacturing Process and Optimization (5 papers), Photonic and Optical Devices (5 papers) and Digital Imaging for Blood Diseases (4 papers). The work is most often cited by research in Cancer Research (127 citations), Sensory Systems (31 citations) and Molecular Biology (412 citations). Xiaonan Yang has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Yongjun Wu, Lihua Ding, Jianhua Miao, Kunhua Wei, Sun Chul Kang, Imran Khan, Ling Kui, Wei Chen, Dawei Li and Min Tang. Their work appears in journals such as IEEE Electron Device Letters, Biosensors and Bioelectronics, Analytical and Bioanalytical Chemistry, IEEE Transactions on Instrumentation and Measurement and Talanta.
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.