Xiaolin Wang
- Biomedical Engineering top 1%
- 3D Printing in Biomedical Research 17
- Advanced Sensor and Energy Harvesting Materials 15
- Innovative Microfluidic and Catalytic Techniques Innovation 11
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- Neuroscience and Neural Engineering 28
- Photoreceptor and optogenetics research 12
- Polymers and Plastics top 5%
- Conducting polymers and applications 8
- Biomaterials top 5%
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function 9
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- Advanced Memory and Neural Computing 6
- Co-authors
- Bin YangJingquan LiuChristopher C.W. HughesDuc T. T. PhanAbraham P. LeeSteven C. GeorgeAgua SobrinoXiang Chen
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Xiaolin Wang
109 papers receiving 3.2k citations
Peers
Comparison fields: 5 of 143
- Biomedical Engineering 1.6k
- Cellular and Molecular Neuroscience 535
- Polymers and Plastics 285
- Biomaterials 248
- Cognitive Neuroscience 296
Countries citing papers authored by Xiaolin Wang
This map shows the geographic impact of Xiaolin 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 Xiaolin Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaolin Wang more than expected).
Fields of papers citing papers by Xiaolin Wang
This network shows the impact of papers produced by Xiaolin 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 Xiaolin Wang. The network helps show where Xiaolin Wang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiaolin 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 | 2024 | 12 | |
| 2 | 2024 | 3 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 9 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 4 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 12 | |
| 9 | 2023 | 10 | |
| 10 | 2023 | 5 | |
| 11 | 2022 | 25 | |
| 12 | 2019 | 24 | |
| 13 | 2017 | 13 | |
| 14 | An Efficient and Effective Online Sentence Segmenter for Simultaneous Interpretation | 2016 | 7 |
| 15 | 2016 | 11 | |
| 16 | 2014 | 21 | |
| 17 | 2013 | 56 | |
| 18 | Spell Checking for Chinese | 2012 | 12 |
| 19 | Enhance Top-down method with Meta-Classification for Very Large-scale Hierarchical Classification | 2011 | 2 |
| 20 | Cross Language Text Categorization Using a Bilingual Lexicon | 2008 | 10 |
About Xiaolin Wang
Xiaolin Wang is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Biomedical Engineering, having authored 113 papers that have together received 3.3k indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (28 papers), 3D Printing in Biomedical Research (17 papers), Advanced Sensor and Energy Harvesting Materials (15 papers), Photoreceptor and optogenetics research (12 papers), Innovative Microfluidic and Catalytic Techniques Innovation (11 papers), Neural dynamics and brain function (9 papers), Conducting polymers and applications (8 papers) and Advanced Memory and Neural Computing (6 papers). The work is most often cited by research in Biomedical Engineering (1.6k citations), Cellular and Molecular Neuroscience (535 citations) and Polymers and Plastics (285 citations). Xiaolin Wang has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Bin Yang, Jingquan Liu, Christopher C.W. Hughes, Duc T. T. Phan, Abraham P. Lee, Steven C. George, Agua Sobrino, Xiang Chen, Bowen Ji and Hongzhuan Chen. Their work appears in journals such as Lab on a Chip, Biosensors and Bioelectronics, ACS Nano, Applied Physics Letters and Journal of Chromatography B.
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.