Dan Yang
Impact in
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- Online Learning and Analytics
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- Context-Aware Activity Recognition Systems
Papers in
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- Advanced Fiber Optic Sensors 20
- Electrical and Bioimpedance Tomography 19
- Photonic Crystal and Fiber Optics 19
- Photonic and Optical Devices 11
- Optical Network Technologies 9
- Co-authors
- Xu Bin (32 shared papers)Weihua Sheng (7 shared papers)Minh Pham (3 shared papers)Meiqin Liu (2 shared papers)Ha Manh (1 shared paper)Xu Wang (23 shared papers)Tonglei Cheng (10 shared papers)Jun Zhu (2 shared papers)
- Journals
- Materials (5 papers)Instrumentation Science & Technology (4 papers)Optical and Quantum Electronics (4 papers)Sensors (4 papers)IEEE Sensors Journal (3 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Dan Yang
102 papers receiving 871 citations
Peers
Comparison fields: 5 of 115
- Computer Science Applications 65
- Computer Vision and Pattern Recognition 204
- Electrical and Electronic Engineering 398
- Computer Networks and Communications 131
- Health Informatics 6
Countries citing papers authored by Dan Yang
This map shows the geographic impact of Dan 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 Dan Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Yang more than expected).
Fields of papers citing papers by Dan Yang
This network shows the impact of papers produced by Dan 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 Dan Yang. The network helps show where Dan Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan 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
Showing the 20 most-cited of 123 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 138 | |
| 2 | 2018 | 65 | |
| 3 | 2016 | 47 | |
| 4 | 2018 | 39 | |
| 5 | 2018 | 39 | |
| 6 | 2020 | 34 | |
| 7 | 2015 | 34 | |
| 8 | 2018 | 29 | |
| 9 | 2018 | 26 | |
| 10 | 2021 | 24 | |
| 11 | 2020 | 23 | |
| 12 | 2015 | 21 | |
| 13 | 2019 | 21 | |
| 14 | 2022 | 14 | |
| 15 | 2023 | 13 | |
| 16 | 2022 | 13 | |
| 17 | 2011 | 13 | |
| 18 | 2006 | 13 | |
| 19 | 2021 | 12 | |
| 20 | 2023 | 12 |
About Dan Yang
Dan Yang is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Control and Systems Engineering, Computer Vision and Pattern Recognition and Mechanical Engineering, having authored 123 papers that have together received 910 indexed citations. Recurring topics across this work include Advanced Fiber Optic Sensors (20 papers), Electrical and Bioimpedance Tomography (19 papers), Photonic Crystal and Fiber Optics (19 papers), Non-Destructive Testing Techniques (12 papers), Photonic and Optical Devices (11 papers), Optical Network Technologies (9 papers), Geophysical and Geoelectrical Methods (9 papers) and Flow Measurement and Analysis (7 papers). The work is most often cited by research in Computer Science Applications (65 citations), Computer Vision and Pattern Recognition (204 citations), Electrical and Electronic Engineering (398 citations), Computer Networks and Communications (131 citations) and Health Informatics (6 citations). Dan Yang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xu Bin, Weihua Sheng, Minh Pham, Meiqin Liu, Ha Manh, Xu Wang, Tonglei Cheng, Jun Zhu, Yanan Zhang and Shihan Xiao. Their work appears in journals such as Materials, Instrumentation Science & Technology, Optical and Quantum Electronics, Sensors and IEEE Sensors Journal.
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.