Yuning Wang
Impact in
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- Model Reduction and Neural Networks
- Computational Mechanics top 10%
- Fluid Dynamics and Turbulent Flows
Papers in
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- GaN-based semiconductor devices and materials 10
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- ZnO doping and properties 5
- Co-authors
- Ricardo Vinuesa (6 shared papers)Carlos Sanmiguel Vila (2 shared papers)Qingquan Lei (1 shared paper)Qingguo Chi (1 shared paper)Changhai Zhang (1 shared paper)Jiaqi Lin (1 shared paper)Gang Liu (1 shared paper)Xuan Wang (1 shared paper)
In The Last Decade
Yuning Wang
18 papers receiving 336 citations
Yuning Wang's Hit Papers
Peers
Comparison fields: 5 of 45
- Statistical and Nonlinear Physics 89
- Computational Mechanics 80
- Electronic, Optical and Magnetic Materials 54
- Biomedical Engineering 119
- Materials Chemistry 125
Countries citing papers authored by Yuning Wang
This map shows the geographic impact of Yuning 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 Yuning Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuning Wang more than expected).
Fields of papers citing papers by Yuning Wang
This network shows the impact of papers produced by Yuning 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 Yuning Wang. The network helps show where Yuning Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Yuning 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 115 | |
| 2 | β-Variational autoencoders and transformers for reduced-order modelling of fluid flows Hit paper breakdown → | 2024 | 90 |
| 3 | 2024 | 37 | |
| 4 | 2023 | 29 | |
| 5 | 2022 | 28 | |
| 6 | 2024 | 7 | |
| 7 | 2022 | 7 | |
| 8 | 2020 | 6 | |
| 9 | 2025 | 4 | |
| 10 | 2024 | 3 | |
| 11 | 2018 | 3 | |
| 12 | 2024 | 2 | |
| 13 | 2023 | 2 | |
| 14 | 2020 | 2 | |
| 15 | 2021 | 1 | |
| 16 | 2025 | 1 | |
| 17 | 2023 | 1 | |
| 18 | 2022 | 1 | |
| 19 | 2023 | 0 | |
| 20 | 2022 | 0 |
About Yuning Wang
Yuning Wang is a scholar working on Condensed Matter Physics, Materials Chemistry, Atomic and Molecular Physics, and Optics, Electronic, Optical and Magnetic Materials and Electrical and Electronic Engineering, having authored 26 papers that have together received 339 indexed citations. Recurring topics across this work include GaN-based semiconductor devices and materials (10 papers), Ga2O3 and related materials (7 papers), ZnO doping and properties (5 papers), Fluid Dynamics and Turbulent Flows (5 papers), Photorefractive and Nonlinear Optics (4 papers), Advanced Fiber Laser Technologies (4 papers), Model Reduction and Neural Networks (4 papers) and Solid State Laser Technologies (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (89 citations), Computational Mechanics (80 citations), Electronic, Optical and Magnetic Materials (54 citations), Biomedical Engineering (119 citations) and Materials Chemistry (125 citations). Yuning Wang has collaborated with scholars based in China, Sweden and Spain. Frequent co-authors include Ricardo Vinuesa, Carlos Sanmiguel Vila, Qingquan Lei, Qingguo Chi, Changhai Zhang, Jiaqi Lin, Gang Liu, Xuan Wang, Scott T. M. Dawson and Hamidreza Eivazi. Their work appears in journals such as International Journal of Heat and Fluid Flow, Japanese Journal of Applied Physics, Nature Communications, Journal of Crystal Growth and Journal of Fluid Mechanics.
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.