Kaiming Ye
Impact in
- Biomaterials top 5%
- Electrospun Nanofibers in Biomedical Applications
- Biomedical Engineering top 5%
- 3D Printing in Biomedical Research
- Graphene and Nanomaterials Applications
Papers in
-
- 3D Printing in Biomedical Research 14
- Graphene and Nanomaterials Applications 5
-
- Pluripotent Stem Cells Research 10
- Viral Infectious Diseases and Gene Expression in Insects 10
- Microbial Metabolic Engineering and Bioproduction 10
- RNA Interference and Gene Delivery 5
- Co-authors
- Sha JinJithesh V. VeetilKazuyuki ShimizuJerome S. SchultzXiuli WangZengmin XiaYanxia ZhuUchechukwu C. Wejinya
- Journals
- Biotechnology Progress (7 papers)Scientific Reports (4 papers)ACS Biomaterials Science & Engineering (3 papers)Journal of Chemical Technology & Biotechnology (3 papers)Journal of Tissue Engineering (2 papers)
- Partner nations
- United StatesJapanChina
In The Last Decade
Kaiming Ye
64 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 133
- Biomaterials 390
- Biomedical Engineering 934
- Automotive Engineering 167
- Molecular Biology 929
- Bioengineering 58
Countries citing papers authored by Kaiming Ye
This map shows the geographic impact of Kaiming Ye'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 Kaiming Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaiming Ye more than expected).
Fields of papers citing papers by Kaiming Ye
This network shows the impact of papers produced by Kaiming Ye. 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 Kaiming Ye. The network helps show where Kaiming Ye may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kaiming Ye, 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 | 1 | |
| 2 | 2024 | 8 | |
| 3 | 2023 | 10 | |
| 4 | 2022 | 47 | |
| 5 | 2022 | 17 | |
| 6 | 2019 | 3 | |
| 7 | 2019 | 108 | |
| 8 | 2018 | 83 | |
| 9 | 2016 | 50 | |
| 10 | 2015 | 2 | |
| 11 | 2013 | 21 | |
| 12 | 2012 | 20 | |
| 13 | 2011 | 13 | |
| 14 | 2011 | 86 | |
| 15 | 2010 | 8 | |
| 16 | 2009 | 58 | |
| 17 | 2008 | 12 | |
| 18 | 2004 | 5 | |
| 19 | 2003 | 20 | |
| 20 | 1996 | 1 |
About Kaiming Ye
Kaiming Ye is a scholar working on Biomedical Engineering, Molecular Biology, Biomaterials, Virology and Automotive Engineering, having authored 64 papers that have together received 2.1k indexed citations. Recurring topics across this work include 3D Printing in Biomedical Research (14 papers), Pancreatic function and diabetes (12 papers), Pluripotent Stem Cells Research (10 papers), Viral Infectious Diseases and Gene Expression in Insects (10 papers), Microbial Metabolic Engineering and Bioproduction (10 papers), Tissue Engineering and Regenerative Medicine (7 papers), RNA Interference and Gene Delivery (5 papers) and Graphene and Nanomaterials Applications (5 papers). The work is most often cited by research in Biomaterials (390 citations), Biomedical Engineering (934 citations), Automotive Engineering (167 citations), Molecular Biology (929 citations) and Bioengineering (58 citations). Kaiming Ye has collaborated with scholars based in United States, Japan and China. Frequent co-authors include Sha Jin, Jithesh V. Veetil, Kazuyuki Shimizu, Sha Jin, Jerome S. Schultz, Xiuli Wang, Zengmin Xia, Yanxia Zhu, Uchechukwu C. Wejinya and Zhuxin Dong. Their work appears in journals such as Biotechnology Progress, Scientific Reports, ACS Biomaterials Science & Engineering, Journal of Chemical Technology & Biotechnology and Journal of Tissue Engineering.
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.