Zi Jun Lin
Impact in
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- Topic Modeling
- Natural Language Processing Techniques
- Speech Recognition and Synthesis
- Machine Learning in Healthcare
Papers in
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- Natural Language Processing Techniques 7
- Topic Modeling 7
- Text Readability and Simplification 2
- Advanced Text Analysis Techniques 1
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- Advanced Image Processing Techniques 2
- Co-authors
- Di He (2 shared papers)Zhuohan Li (2 shared papers)Tiantian Zhu (1 shared paper)Lei Fu (1 shared paper)Tieming Chen (1 shared paper)Liwei Wang (1 shared paper)Fei Tian (1 shared paper)Tie‐Yan Liu (1 shared paper)
- Journals
- Journal of Clinical Medicine (1 paper)IEEE Transactions on Information Forensics and Security (1 paper)Computational Linguistics (1 paper)Scientific Reports (1 paper)Materials science forum (2 papers)
- Partner nations
- ChinaUnited StatesIsrael
In The Last Decade
Zi Jun Lin
14 papers receiving 179 citations
Peers
Comparison fields: 5 of 59
- Health Informatics 6
- Artificial Intelligence 107
- Computer Vision and Pattern Recognition 59
- Signal Processing 16
- Human-Computer Interaction 7
Countries citing papers authored by Zi Jun Lin
This map shows the geographic impact of Zi Jun Lin'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 Zi Jun Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zi Jun Lin more than expected).
Fields of papers citing papers by Zi Jun Lin
This network shows the impact of papers produced by Zi Jun Lin. 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 Zi Jun Lin. The network helps show where Zi Jun Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Zi Jun Lin, 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 | 2019 | 35 | |
| 2 | 2020 | 33 | |
| 3 | 2020 | 27 | |
| 4 | Fast Structured Decoding for Sequence Models | 2019 | 25 |
| 5 | 2020 | 21 | |
| 6 | 2022 | 12 | |
| 7 | 2019 | 11 | |
| 8 | 2019 | 4 | |
| 9 | 2019 | 4 | |
| 10 | 2018 | 4 | |
| 11 | 2019 | 2 | |
| 12 | 2019 | 2 | |
| 13 | 2021 | 2 | |
| 14 | 2020 | 1 |
About Zi Jun Lin
Zi Jun Lin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Health Information Management, Statistics and Probability and Media Technology, having authored 14 papers that have together received 183 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (7 papers), Topic Modeling (7 papers), Advanced Image Processing Techniques (2 papers), Text Readability and Simplification (2 papers), Medical Imaging Techniques and Applications (1 paper), Advanced Fiber Optic Sensors (1 paper), Advanced Text Analysis Techniques (1 paper) and Gait Recognition and Analysis (1 paper). The work is most often cited by research in Health Informatics (6 citations), Artificial Intelligence (107 citations), Computer Vision and Pattern Recognition (59 citations), Signal Processing (16 citations) and Human-Computer Interaction (7 citations). Zi Jun Lin has collaborated with scholars based in China, United States and Israel. Frequent co-authors include Di He, Zhuohan Li, Tiantian Zhu, Lei Fu, Tieming Chen, Liwei Wang, Fei Tian, Tie‐Yan Liu, Tao Qin and Zhiqing Sun. Their work appears in journals such as Journal of Clinical Medicine, IEEE Transactions on Information Forensics and Security, Computational Linguistics, Scientific Reports and Materials science forum.
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.