Wei-Jen Ko
Impact in
- Artificial Intelligence top 10%
- Text and Document Classification Technologies
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
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- Multimodal Machine Learning Applications
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
Papers in
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- Natural Language Processing Techniques 8
- Topic Modeling 8
- Speech and dialogue systems 3
- Text Readability and Simplification 2
- Speech Recognition and Synthesis 2
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- Multimodal Machine Learning Applications 1
- Advanced Vision and Imaging 1
- Image and Signal Denoising Methods 1
- Co-authors
- Chih‐Kuan Yeh (1 shared paper)Yu-Chiang Frank Wang (1 shared paper)Greg Durrett (5 shared papers)Junyi Jessy Li (5 shared papers)Shao‐Yi Chien (1 shared paper)Philipp Koehn (1 shared paper)Adithya Renduchintala (1 shared paper)Vishrav Chaudhary (1 shared paper)
- Journals
- Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)Rare & Special e-Zone (The Hong Kong University of Science and Technology) (1 paper)
- Partner nations
- United StatesTaiwanHong Kong
In The Last Decade
Wei-Jen Ko
10 papers receiving 229 citations
Peers
Comparison fields: 5 of 45
- Artificial Intelligence 196
- Computer Vision and Pattern Recognition 84
- Signal Processing 19
- Information Systems 38
- Media Technology 5
Countries citing papers authored by Wei-Jen Ko
This map shows the geographic impact of Wei-Jen Ko'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 Wei-Jen Ko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei-Jen Ko more than expected).
Fields of papers citing papers by Wei-Jen Ko
This network shows the impact of papers produced by Wei-Jen Ko. 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 Wei-Jen Ko. The network helps show where Wei-Jen Ko may publish in the future.
Co-authors
The 20 scholars most cited alongside Wei-Jen Ko, 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 | 2017 | 158 | |
| 2 | 2020 | 23 | |
| 3 | 2021 | 17 | |
| 4 | 2019 | 13 | |
| 5 | 2019 | 5 | |
| 6 | 2020 | 4 | |
| 7 | 2017 | 4 | |
| 8 | 2016 | 3 | |
| 9 | 2023 | 3 | |
| 10 | 2022 | 1 |
About Wei-Jen Ko
Wei-Jen Ko is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Infectious Diseases, Organic Chemistry and Surgery, having authored 10 papers that have together received 231 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (8 papers), Topic Modeling (8 papers), Speech and dialogue systems (3 papers), Text Readability and Simplification (2 papers), Speech Recognition and Synthesis (2 papers), Multimodal Machine Learning Applications (1 paper), Advanced Vision and Imaging (1 paper) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Artificial Intelligence (196 citations), Computer Vision and Pattern Recognition (84 citations), Signal Processing (19 citations), Information Systems (38 citations) and Media Technology (5 citations). Wei-Jen Ko has collaborated with scholars based in United States, Taiwan and Hong Kong. Frequent co-authors include Chih‐Kuan Yeh, Yu-Chiang Frank Wang, Greg Durrett, Junyi Jessy Li, Shao‐Yi Chien, Philipp Koehn, Adithya Renduchintala, Vishrav Chaudhary, Naman Goyal and Pascale Fung. Their work appears in journals such as Proceedings of the AAAI Conference on Artificial Intelligence and Rare & Special e-Zone (The Hong Kong University of Science and Technology).
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.