Ya Su
- Signal Processing top 1%
- Artificial Intelligence top 1%
- Biomedical Engineering top 5%
- 3D Printing in Biomedical Research 8
- Bone Tissue Engineering Materials 5
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- Electrospun Nanofibers in Biomedical Applications 8
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- Tissue Engineering and Regenerative Medicine 7
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- Advanced biosensing and bioanalysis techniques 7
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- Carbon and Quantum Dots Applications 7
- Nanocluster Synthesis and Applications 5
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- Spacecraft Dynamics and Control 5
- Co-authors
- Dan PeiYoujian ZhaoWei SunRong LiuChenhao NiuMin ZhengZhigang XieXidao Wen
- Journals
- International Journal of Biological Macromolecules (7 papers)Biofabrication (4 papers)Aerospace Science and Technology (2 papers)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Ya Su
52 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 149
- Signal Processing 611
- Artificial Intelligence 1.0k
- Computer Networks and Communications 699
- Biomedical Engineering 481
- Control and Systems Engineering 213
Countries citing papers authored by Ya Su
This map shows the geographic impact of Ya Su'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 Ya Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ya Su more than expected).
Fields of papers citing papers by Ya Su
This network shows the impact of papers produced by Ya Su. 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 Ya Su. The network helps show where Ya Su may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ya Su, 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 | 3 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 1 | |
| 8 | 2024 | 4 | |
| 9 | 2023 | 25 | |
| 10 | 2023 | 10 | |
| 11 | 2023 | 1 | |
| 12 | 2023 | 1 | |
| 13 | 2023 | 6 | |
| 14 | 2022 | 25 | |
| 15 | 2022 | 31 | |
| 16 | 2022 | 14 | |
| 17 | 2021 | 30 | |
| 18 | 2019 | 57 | |
| 19 | 2017 | 8 | |
| 20 | 2012 | 45 |
About Ya Su
Ya Su is a scholar working on Biomaterials, Biomedical Engineering and Biophysics, having authored 56 papers that have together received 2.1k indexed citations. Recurring topics across this work include 3D Printing in Biomedical Research (8 papers), Electrospun Nanofibers in Biomedical Applications (8 papers), Tissue Engineering and Regenerative Medicine (7 papers), Advanced biosensing and bioanalysis techniques (7 papers), Carbon and Quantum Dots Applications (7 papers), Nanocluster Synthesis and Applications (5 papers), Spacecraft Dynamics and Control (5 papers) and Bone Tissue Engineering Materials (5 papers). The work is most often cited by research in Signal Processing (611 citations), Artificial Intelligence (1.0k citations) and Computer Networks and Communications (699 citations). Ya Su has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Dan Pei, Youjian Zhao, Wei Sun, Rong Liu, Chenhao Niu, Min Zheng, Zhigang Xie, Xidao Wen, Shi Liu and Rui Jiao. Their work appears in journals such as International Journal of Biological Macromolecules, Biofabrication, Aerospace Science and Technology, Soft Computing and Analytical Chemistry.
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.