Chengjun Chen
Impact in
- Biomaterials top 1%
- Nanoparticle-Based Drug Delivery
- Supramolecular Self-Assembly in Materials
- Drug Discovery top 10%
Papers in
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- Industrial Vision Systems and Defect Detection 13
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- Advanced Neural Network Applications 15
- Augmented Reality Applications 4
- Co-authors
- Xuehai Yan (8 shared papers)Xing Tang (3 shared papers)Dandan Han (3 shared papers)Guanghui Ma (5 shared papers)Ruirui Xing (5 shared papers)Cuifang Cai (1 shared paper)Guizhi Shen (5 shared papers)Dongnian Li (18 shared papers)
In The Last Decade
Chengjun Chen
61 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 117
- Biomaterials 752
- Drug Discovery 8
- Pharmaceutical Science 165
- Industrial and Manufacturing Engineering 157
- Biomedical Engineering 380
Countries citing papers authored by Chengjun Chen
This map shows the geographic impact of Chengjun Chen'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 Chengjun Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chengjun Chen more than expected).
Fields of papers citing papers by Chengjun Chen
This network shows the impact of papers produced by Chengjun Chen. 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 Chengjun Chen. The network helps show where Chengjun Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Chengjun Chen, 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 68 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 454 | |
| 2 | 2016 | 308 | |
| 3 | 2014 | 282 | |
| 4 | 2016 | 188 | |
| 5 | 2009 | 104 | |
| 6 | 2014 | 89 | |
| 7 | 2023 | 79 | |
| 8 | 2020 | 76 | |
| 9 | 2012 | 75 | |
| 10 | 2016 | 70 | |
| 11 | 2015 | 68 | |
| 12 | 2016 | 65 | |
| 13 | 2023 | 48 | |
| 14 | 2021 | 44 | |
| 15 | 2020 | 38 | |
| 16 | 2020 | 36 | |
| 17 | 2020 | 27 | |
| 18 | 2020 | 27 | |
| 19 | 2009 | 25 | |
| 20 | 2020 | 23 |
About Chengjun Chen
Chengjun Chen is a scholar working on Industrial and Manufacturing Engineering, Computer Vision and Pattern Recognition, Biomaterials, Control and Systems Engineering and Mechanical Engineering, having authored 68 papers that have together received 2.4k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (15 papers), Industrial Vision Systems and Defect Detection (13 papers), Robot Manipulation and Learning (10 papers), Teleoperation and Haptic Systems (8 papers), Nanoparticle-Based Drug Delivery (8 papers), Augmented Reality Applications (4 papers), Reinforcement Learning in Robotics (3 papers) and Nanoplatforms for cancer theranostics (3 papers). The work is most often cited by research in Biomaterials (752 citations), Drug Discovery (8 citations), Pharmaceutical Science (165 citations), Industrial and Manufacturing Engineering (157 citations) and Biomedical Engineering (380 citations). Chengjun Chen has collaborated with scholars based in China, Singapore and Germany. Frequent co-authors include Xuehai Yan, Xing Tang, Dandan Han, Guanghui Ma, Ruirui Xing, Cuifang Cai, Guizhi Shen, Dongnian Li, Kai Liu and Tifeng Jiao. Their work appears in journals such as The International Journal of Advanced Manufacturing Technology, Robotics and Computer-Integrated Manufacturing, Measurement, Sensors and Review of Scientific Instruments.
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.