Sangwu Lee
Impact in
- Artificial Intelligence top 5%
- Sentiment Analysis and Opinion Mining
- Topic Modeling
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
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- Emotion and Mood Recognition
Papers in
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- Parkinson's Disease Mechanisms and Treatments 4
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- Deception detection and forensic psychology 1
- Co-authors
- Ehsan Hoque (6 shared papers)Wasifur Rahman (6 shared papers)Louis–Philippe Morency (2 shared papers)Md. Kamrul Hasan (1 shared paper)AmirAli Bagher Zadeh (1 shared paper)Chengfeng Mao (1 shared paper)Amir Zadeh (1 shared paper)Rada Mihalcea (1 shared paper)
- Journals
- npj Digital Medicine (1 paper)Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (1 paper)NEJM AI (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)PubMed (1 paper)
- Partner nations
- United StatesBangladeshUnited Kingdom
In The Last Decade
Sangwu Lee
6 papers receiving 423 citations
Sangwu Lee's Hit Papers
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 319
- Experimental and Cognitive Psychology 121
- Signal Processing 73
- Computational Mathematics 4
- Computer Vision and Pattern Recognition 120
Countries citing papers authored by Sangwu Lee
This map shows the geographic impact of Sangwu Lee'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 Sangwu Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sangwu Lee more than expected).
Fields of papers citing papers by Sangwu Lee
This network shows the impact of papers produced by Sangwu Lee. 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 Sangwu Lee. The network helps show where Sangwu Lee may publish in the future.
Co-authors
The 17 scholars most cited alongside Sangwu Lee, 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 | Integrating Multimodal Information in Large Pretrained Transformers Hit paper breakdown → | 2020 | 351 |
| 2 | 2021 | 45 | |
| 3 | 2023 | 26 | |
| 4 | 2019 | 6 | |
| 5 | 2023 | 4 | |
| 6 | 2025 | 2 | |
| 7 | 2025 | 0 |
About Sangwu Lee
Sangwu Lee is a scholar working on Neurology, Social Psychology, Physiology, Occupational Therapy and Sociology and Political Science, having authored 7 papers that have together received 434 indexed citations. Recurring topics across this work include Parkinson's Disease Mechanisms and Treatments (4 papers), Voice and Speech Disorders (2 papers), Natural Language Processing Techniques (1 paper), Multimodal Machine Learning Applications (1 paper), Misinformation and Its Impacts (1 paper), Autism Spectrum Disorder Research (1 paper), Speech and dialogue systems (1 paper) and Deception detection and forensic psychology (1 paper). The work is most often cited by research in Artificial Intelligence (319 citations), Experimental and Cognitive Psychology (121 citations), Signal Processing (73 citations), Computational Mathematics (4 citations) and Computer Vision and Pattern Recognition (120 citations). Sangwu Lee has collaborated with scholars based in United States, Bangladesh and United Kingdom. Frequent co-authors include Ehsan Hoque, Wasifur Rahman, Louis–Philippe Morency, Md. Kamrul Hasan, AmirAli Bagher Zadeh, Chengfeng Mao, Amir Zadeh, Rada Mihalcea, Jamie Adams and Md. Saiful Islam. Their work appears in journals such as npj Digital Medicine, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, NEJM AI, Proceedings of the AAAI Conference on Artificial Intelligence and PubMed.
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.