Will Ke Wang
Impact in
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- Astronomy and Astrophysical Research
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- Time Series Analysis and Forecasting
Papers in
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- EEG and Brain-Computer Interfaces 2
- Tactile and Sensory Interactions 2
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- Advanced Sensor and Energy Harvesting Materials 2
- Co-authors
- Jessilyn Dunn (6 shared papers)Brinnae Bent (2 shared papers)Stephen J. Redmond (1 shared paper)G. Schreier (1 shared paper)Michael Schukat (1 shared paper)Jeffrey E. Olgin (1 shared paper)Robert Avram (1 shared paper)Nigel H. Lovell (1 shared paper)
- Journals
- Sensors (2 papers)Journal of Medical Internet Research (2 papers)Materials Science and Engineering R Reports (1 paper)Signal Processing (1 paper)Biomedical Signal Processing and Control (1 paper)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Will Ke Wang
12 papers receiving 148 citations
Peers
Comparison fields: 5 of 93
- Instrumentation 10
- Signal Processing 26
- Applied Psychology 10
- Health Information Management 7
- Health Informatics 2
Countries citing papers authored by Will Ke Wang
This map shows the geographic impact of Will Ke Wang'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 Will Ke Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Will Ke Wang more than expected).
Fields of papers citing papers by Will Ke Wang
This network shows the impact of papers produced by Will Ke Wang. 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 Will Ke Wang. The network helps show where Will Ke Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Will Ke Wang, 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 | 2016 | 41 | |
| 2 | 2020 | 39 | |
| 3 | 2022 | 23 | |
| 4 | 2020 | 21 | |
| 5 | 2021 | 8 | |
| 6 | 2021 | 8 | |
| 7 | 2022 | 5 | |
| 8 | 2024 | 4 | |
| 9 | 2023 | 3 | |
| 10 | 2025 | 2 | |
| 11 | 2025 | 1 | |
| 12 | 2025 | 1 | |
| 13 | 2025 | 0 | |
| 14 | 2025 | 0 |
About Will Ke Wang
Will Ke Wang is a scholar working on Cognitive Neuroscience, Biomedical Engineering, Signal Processing, Cellular and Molecular Neuroscience and Dermatology, having authored 14 papers that have together received 156 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (3 papers), EEG and Brain-Computer Interfaces (2 papers), Tactile and Sensory Interactions (2 papers), Advanced Sensor and Energy Harvesting Materials (2 papers), Radar Systems and Signal Processing (1 paper), MicroRNA in disease regulation (1 paper), Urticaria and Related Conditions (1 paper) and Neuroscience and Neural Engineering (1 paper). The work is most often cited by research in Instrumentation (10 citations), Signal Processing (26 citations), Applied Psychology (10 citations), Health Information Management (7 citations) and Health Informatics (2 citations). Will Ke Wang has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Jessilyn Dunn, Brinnae Bent, Stephen J. Redmond, G. Schreier, Michael Schukat, Jeffrey E. Olgin, Robert Avram, Nigel H. Lovell, Michael Marschollek and Md Mobashir Hasan Shandhi. Their work appears in journals such as Sensors, Journal of Medical Internet Research, Materials Science and Engineering R Reports, Signal Processing and Biomedical Signal Processing and Control.
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.