Liangchen Luo
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Stochastic Gradient Optimization Techniques
- Speech and dialogue systems
- Natural Language Processing Techniques
- Machine Learning and ELM
- Neural Networks and Applications
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- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
Papers in
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- Natural Language Processing Techniques 3
- Topic Modeling 3
- Speech and dialogue systems 3
- Semantic Web and Ontologies 1
- Multi-Agent Systems and Negotiation 1
- Co-authors
- Yan Liu (1 shared paper)Yuanhao Xiong (1 shared paper)Xu Sun (1 shared paper)Qi Zeng (2 shared papers)Xu Sun (2 shared papers)Zaiqing Nie (1 shared paper)Jingjing Xu (1 shared paper)Junyang Lin (1 shared paper)
- Journals
- Proceedings of the AAAI Conference on Artificial Intelligence (2 papers)arXiv (Cornell University) (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Liangchen Luo
7 papers receiving 170 citations
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 134
- Computer Vision and Pattern Recognition 53
- Human-Computer Interaction 5
- Space and Planetary Science 1
- Health Informatics 1
Countries citing papers authored by Liangchen Luo
This map shows the geographic impact of Liangchen Luo'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 Liangchen Luo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liangchen Luo more than expected).
Fields of papers citing papers by Liangchen Luo
This network shows the impact of papers produced by Liangchen Luo. 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 Liangchen Luo. The network helps show where Liangchen Luo may publish in the future.
Co-authors
The 23 scholars most cited alongside Liangchen Luo, 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 | 96 | |
| 2 | 2019 | 46 | |
| 3 | 2018 | 21 | |
| 4 | 2024 | 10 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 1 |
About Liangchen Luo
Liangchen Luo is a scholar working on Artificial Intelligence, Political Science and International Relations, Management Information Systems, Computer Vision and Pattern Recognition and Management of Technology and Innovation, having authored 7 papers that have together received 177 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (3 papers), Topic Modeling (3 papers), Speech and dialogue systems (3 papers), Business Process Modeling and Analysis (1 paper), Semantic Web and Ontologies (1 paper), Collaboration in agile enterprises (1 paper), Multi-Agent Systems and Negotiation (1 paper) and Robotic Process Automation Applications (1 paper). The work is most often cited by research in Artificial Intelligence (134 citations), Computer Vision and Pattern Recognition (53 citations), Human-Computer Interaction (5 citations), Space and Planetary Science (1 citation) and Health Informatics (1 citation). Liangchen Luo has collaborated with scholars based in China and United States. Frequent co-authors include Yan Liu, Yuanhao Xiong, Xu Sun, Qi Zeng, Xu Sun, Zaiqing Nie, Jingjing Xu, Junyang Lin, Lei Shu and Lei Meng. Their work appears in journals such as Proceedings of the AAAI Conference on Artificial Intelligence and arXiv (Cornell University).
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.