Rujun Han
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Advanced Graph Neural Networks
- Speech and dialogue systems
- Semantic Web and Ontologies
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- Multimodal Machine Learning Applications
Papers in
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- Topic Modeling 13
- Natural Language Processing Techniques 9
- Advanced Text Analysis Techniques 3
- Speech and dialogue systems 2
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- Multimodal Machine Learning Applications 6
- Co-authors
- Nanyun Peng (10 shared papers)Ning Qiang (2 shared papers)Dan Roth (3 shared papers)Mu Yang (2 shared papers)Yichao Zhou (1 shared paper)Hao Wu (1 shared paper)Matt Gardner (1 shared paper)Aram Galstyan (2 shared papers)
- Journals
- Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2 papers)Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)International Conference of Learning Sciences (1 paper)
- Partner nations
- United StatesChinaSwitzerland
In The Last Decade
Rujun Han
16 papers receiving 288 citations
Peers
Comparison fields: 5 of 29
- Artificial Intelligence 266
- Computer Vision and Pattern Recognition 58
- Management Science and Operations Research 32
- General Social Sciences 7
- Signal Processing 20
Countries citing papers authored by Rujun Han
This map shows the geographic impact of Rujun Han'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 Rujun Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rujun Han more than expected).
Fields of papers citing papers by Rujun Han
This network shows the impact of papers produced by Rujun Han. 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 Rujun Han. The network helps show where Rujun Han may publish in the future.
Co-authors
The 25 scholars most cited alongside Rujun Han, 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 | 78 | |
| 2 | 2020 | 40 | |
| 3 | 2019 | 37 | |
| 4 | 2020 | 25 | |
| 5 | 2021 | 23 | |
| 6 | 2021 | 19 | |
| 7 | 2021 | 18 | |
| 8 | 2021 | 14 | |
| 9 | 2022 | 11 | |
| 10 | 2021 | 7 | |
| 11 | 2024 | 6 | |
| 12 | 2018 | 6 | |
| 13 | 2022 | 6 | |
| 14 | 2020 | 2 | |
| 15 | 2023 | 1 | |
| 16 | 2023 | 1 | |
| 17 | 2025 | 0 |
About Rujun Han
Rujun Han is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Management Science and Operations Research and Molecular Biology, having authored 17 papers that have together received 294 indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Natural Language Processing Techniques (9 papers), Multimodal Machine Learning Applications (6 papers), Advanced Text Analysis Techniques (3 papers), Speech and dialogue systems (2 papers), Data Quality and Management (2 papers), Time Series Analysis and Forecasting (1 paper) and Expert finding and Q&A systems (1 paper). The work is most often cited by research in Artificial Intelligence (266 citations), Computer Vision and Pattern Recognition (58 citations), Management Science and Operations Research (32 citations), General Social Sciences (7 citations) and Signal Processing (20 citations). Rujun Han has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Nanyun Peng, Ning Qiang, Dan Roth, Mu Yang, Yichao Zhou, Hao Wu, Matt Gardner, Aram Galstyan, Ralph Weischedel and Jiao Sun. Their work appears in journals such as Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the AAAI Conference on Artificial Intelligence and International Conference of Learning Sciences.
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.