Tiejun Li
Impact in
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- Robotic Path Planning Algorithms
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- Advanced Measurement and Metrology Techniques
- Aluminum Alloys Composites Properties
- Advanced machining processes and optimization
Papers in
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- Robotic Mechanisms and Dynamics 12
- Robot Manipulation and Learning 7
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- Soft Robotics and Applications 5
- Co-authors
- Kewen Xia (4 shared papers)Yuqing Peng (2 shared papers)Jiangnan Zhang (2 shared papers)Wang Li (1 shared paper)Yu Feng (1 shared paper)Hai‐Tao Liu (2 shared papers)Shurui Fan (1 shared paper)Sujun Wu (1 shared paper)
- Journals
- The International Journal of Advanced Manufacturing Technology (4 papers)IEEE Access (2 papers)Sensors (2 papers)Engineering Applications of Artificial Intelligence (1 paper)Chinese Journal of Mechanical Engineering (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Tiejun Li
39 papers receiving 454 citations
Peers
Comparison fields: 5 of 89
- Computer Vision and Pattern Recognition 110
- Mechanical Engineering 160
- Computational Mathematics 2
- Control and Systems Engineering 76
- Artificial Intelligence 99
Countries citing papers authored by Tiejun Li
This map shows the geographic impact of Tiejun Li'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 Tiejun Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tiejun Li more than expected).
Fields of papers citing papers by Tiejun Li
This network shows the impact of papers produced by Tiejun Li. 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 Tiejun Li. The network helps show where Tiejun Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Tiejun Li, 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 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 88 | |
| 2 | 2021 | 51 | |
| 3 | 2005 | 46 | |
| 4 | 2017 | 35 | |
| 5 | 2021 | 31 | |
| 6 | 2017 | 28 | |
| 7 | 2020 | 21 | |
| 8 | 2017 | 19 | |
| 9 | 2021 | 19 | |
| 10 | 2021 | 15 | |
| 11 | 2021 | 15 | |
| 12 | 2019 | 10 | |
| 13 | 2017 | 10 | |
| 14 | 2018 | 8 | |
| 15 | 2017 | 8 | |
| 16 | 2009 | 7 | |
| 17 | 2020 | 7 | |
| 18 | 2021 | 5 | |
| 19 | 2021 | 5 | |
| 20 | 2020 | 4 |
About Tiejun Li
Tiejun Li is a scholar working on Control and Systems Engineering, Biomedical Engineering, Mechanical Engineering, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 45 papers that have together received 471 indexed citations. Recurring topics across this work include Robotic Mechanisms and Dynamics (12 papers), Robot Manipulation and Learning (7 papers), Soft Robotics and Applications (5 papers), Advanced Measurement and Metrology Techniques (5 papers), Robotic Path Planning Algorithms (5 papers), Advanced machining processes and optimization (4 papers), 3D Surveying and Cultural Heritage (3 papers) and Optical measurement and interference techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (110 citations), Mechanical Engineering (160 citations), Computational Mathematics (2 citations), Control and Systems Engineering (76 citations) and Artificial Intelligence (99 citations). Tiejun Li has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Kewen Xia, Yuqing Peng, Jiangnan Zhang, Wang Li, Yu Feng, Hai‐Tao Liu, Shurui Fan, Sujun Wu, Hongliang Hou and Yaoqi Wang. Their work appears in journals such as The International Journal of Advanced Manufacturing Technology, IEEE Access, Sensors, Engineering Applications of Artificial Intelligence and Chinese Journal of Mechanical 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.