Boyu Wang
Impact in
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Signal Processing top 5%
- Blind Source Separation Techniques
Papers in
-
- Domain Adaptation and Few-Shot Learning 22
- Machine Learning and ELM 5
-
- EEG and Brain-Computer Interfaces 18
- Neural dynamics and brain function 8
- Co-authors
- Feng Wan (18 shared papers)Chi Man Wong (12 shared papers)Agostinho Rosa (4 shared papers)Ze Wang (3 shared papers)Peng Un Mak (13 shared papers)Mang I Vai (13 shared papers)Changjian Shui (8 shared papers)Fan Zhou (8 shared papers)
In The Last Decade
Boyu Wang
63 papers receiving 922 citations
Peers
Comparison fields: 5 of 106
- Cognitive Neuroscience 449
- Signal Processing 117
- Cellular and Molecular Neuroscience 185
- Artificial Intelligence 303
- Human-Computer Interaction 51
Countries citing papers authored by Boyu Wang
This map shows the geographic impact of Boyu 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 Boyu Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Boyu Wang more than expected).
Fields of papers citing papers by Boyu Wang
This network shows the impact of papers produced by Boyu 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 Boyu Wang. The network helps show where Boyu Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Boyu 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
Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 102 | |
| 2 | 2020 | 98 | |
| 3 | 2020 | 63 | |
| 4 | 2021 | 51 | |
| 5 | 2022 | 49 | |
| 6 | 2019 | 46 | |
| 7 | 2011 | 43 | |
| 8 | 2022 | 33 | |
| 9 | 2022 | 29 | |
| 10 | 2009 | 26 | |
| 11 | 2023 | 26 | |
| 12 | 2015 | 21 | |
| 13 | 2020 | 21 | |
| 14 | Transfer Learning via Minimizing the Performance Gap Between Domains | 2019 | 18 |
| 15 | 2018 | 18 | |
| 16 | 2022 | 18 | |
| 17 | 2021 | 18 | |
| 18 | 2020 | 17 | |
| 19 | 2013 | 17 | |
| 20 | 2023 | 16 |
About Boyu Wang
Boyu Wang is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Computer Vision and Pattern Recognition, Cellular and Molecular Neuroscience and Signal Processing, having authored 69 papers that have together received 944 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (22 papers), EEG and Brain-Computer Interfaces (18 papers), Multimodal Machine Learning Applications (11 papers), Neural dynamics and brain function (8 papers), Blind Source Separation Techniques (5 papers), Neuroscience and Neural Engineering (5 papers), Machine Learning and ELM (5 papers) and Human Pose and Action Recognition (4 papers). The work is most often cited by research in Cognitive Neuroscience (449 citations), Signal Processing (117 citations), Cellular and Molecular Neuroscience (185 citations), Artificial Intelligence (303 citations) and Human-Computer Interaction (51 citations). Boyu Wang has collaborated with scholars based in Canada, China and Macao. Frequent co-authors include Feng Wan, Chi Man Wong, Agostinho Rosa, Ze Wang, Peng Un Mak, Mang I Vai, Changjian Shui, Fan Zhou, Pui‐In Mak and Wenya Nan. Their work appears in journals such as Knowledge-Based Systems, Neural Networks, Journal of Neuroscience, European Heart Journal - Quality of Care and Clinical Outcomes and Neurocomputing.
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.