Xingyu Wang
- Human-Computer Interaction top 2%
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces 18
- Materials Chemistry top 5%
- Corrosion Behavior and Inhibition 16
- Graphene research and applications 9
- Nanocluster Synthesis and Applications 8
- Signal Processing top 5%
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- Tribology and Wear Analysis 10
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- Neuroscience and Neural Engineering 10
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- Concrete Corrosion and Durability 9
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- Advanced Memory and Neural Computing 8
- Cited by
- Renewable Energy, Sustainability and the EnvironmentHuman-Computer InteractionCognitive Neuroscience
- Journals
- Progress in Organic Coatings (5 papers)IEEE Transactions on Neural Systems and Rehabilitation Engineering (4 papers)Polymer Composites (4 papers)
- Partner nations
- ChinaUnited StatesPoland
In The Last Decade
Xingyu Wang
157 papers receiving 3.0k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Renewable Energy, Sustainability and the Environment 565
- Human-Computer Interaction 179
- Cognitive Neuroscience 598
- Materials Chemistry 915
- Signal Processing 169
Countries citing papers authored by Xingyu Wang
This map shows the geographic impact of Xingyu 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 Xingyu Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xingyu Wang more than expected).
Fields of papers citing papers by Xingyu Wang
This network shows the impact of papers produced by Xingyu 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 Xingyu Wang. The network helps show where Xingyu Wang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xingyu 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 | 2025 | 0 | |
| 2 | 2025 | 3 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 2 | |
| 5 | 2025 | 4 | |
| 6 | 2025 | 1 | |
| 7 | 2025 | 0 | |
| 8 | 2024 | 22 | |
| 9 | 2024 | 9 | |
| 10 | 2024 | 7 | |
| 11 | 2024 | 4 | |
| 12 | 2024 | 0 | |
| 13 | 2024 | 14 | |
| 14 | 2024 | 2 | |
| 15 | 2024 | 1 | |
| 16 | 2023 | 5 | |
| 17 | Internal Feature Selection Method of CSP Based on L1-Norm and Dempster–Shafer Theorybreakdown → | 2020 | 216 |
| 18 | 2020 | 109 | |
| 19 | 2018 | 127 | |
| 20 | Feature Extraction and Classification for Short-Time Sleep | 2011 | 2 |
About Xingyu Wang
Xingyu Wang is a scholar working on Metals and Alloys, Civil and Structural Engineering and Mechanics of Materials, having authored 173 papers that have together received 3.0k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (18 papers), Corrosion Behavior and Inhibition (16 papers), Tribology and Wear Analysis (10 papers), Neuroscience and Neural Engineering (10 papers), Concrete Corrosion and Durability (9 papers), Graphene research and applications (9 papers), Advanced Memory and Neural Computing (8 papers) and Nanocluster Synthesis and Applications (8 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (565 citations), Human-Computer Interaction (179 citations) and Cognitive Neuroscience (598 citations). Xingyu Wang has collaborated with scholars based in China, United States and Poland. Frequent co-authors include Zhibin Lin, Jing Jin, Andrzej Cichocki, Ian Daly, Yangyang Miao, Xiaoning Qi, Hong Pan, Hongji Liu, Hui Wang and Hui Wang. Their work appears in journals such as Progress in Organic Coatings, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Polymer Composites, Sensors and ACS ES&T Water.
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.