Lanbo She
Impact in
- Artificial Intelligence top 5%
- Speech and dialogue systems
- Natural Language Processing Techniques
- Topic Modeling
- AI-based Problem Solving and Planning
- Reinforcement Learning in Robotics
-
- Multimodal Machine Learning Applications
Papers in
-
- Speech and dialogue systems 7
- Topic Modeling 6
- Natural Language Processing Techniques 5
- AI-based Problem Solving and Planning 4
- Semantic Web and Ontologies 1
-
- Robot Manipulation and Learning 4
- Robotics and Automated Systems 1
- Co-authors
- Joyce Chai (12 shared papers)Rui Fang (7 shared papers)Changsong Liu (5 shared papers)Yunyi Jia (5 shared papers)Ning Xi (5 shared papers)Yu Cheng (1 shared paper)Yu Cheng (4 shared papers)Kenneth Hanson (1 shared paper)
- Journals
- AI Magazine (1 paper)Annual Meeting of the Special Interest Group on Discourse and Dialogue (1 paper)The HKU Scholars Hub (University of Hong Kong) (1 paper)IFAC Proceedings Volumes (1 paper)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Lanbo She
13 papers receiving 266 citations
Peers
Comparison fields: 5 of 33
- Artificial Intelligence 217
- Computer Vision and Pattern Recognition 97
- Control and Systems Engineering 93
- Social Psychology 49
- Cultural Studies 14
Countries citing papers authored by Lanbo She
This map shows the geographic impact of Lanbo She'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 Lanbo She with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lanbo She more than expected).
Fields of papers citing papers by Lanbo She
This network shows the impact of papers produced by Lanbo She. 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 Lanbo She. The network helps show where Lanbo She may publish in the future.
Co-authors
The 13 scholars most cited alongside Lanbo She, 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 | 2014 | 57 | |
| 2 | 2014 | 47 | |
| 3 | 2014 | 33 | |
| 4 | 2017 | 26 | |
| 5 | 2016 | 24 | |
| 6 | 2013 | 20 | |
| 7 | 2013 | 17 | |
| 8 | 2014 | 13 | |
| 9 | 2016 | 12 | |
| 10 | 2016 | 11 | |
| 11 | 2014 | 8 | |
| 12 | 2014 | 7 | |
| 13 | 2009 | 5 |
About Lanbo She
Lanbo She is a scholar working on Artificial Intelligence, Control and Systems Engineering, Computer Vision and Pattern Recognition, Social Psychology and Computational Theory and Mathematics, having authored 13 papers that have together received 280 indexed citations. Recurring topics across this work include Speech and dialogue systems (7 papers), Topic Modeling (6 papers), Natural Language Processing Techniques (5 papers), AI-based Problem Solving and Planning (4 papers), Robot Manipulation and Learning (4 papers), Semantic Web and Ontologies (1 paper), Face and Expression Recognition (1 paper) and Robotics and Automated Systems (1 paper). The work is most often cited by research in Artificial Intelligence (217 citations), Computer Vision and Pattern Recognition (97 citations), Control and Systems Engineering (93 citations), Social Psychology (49 citations) and Cultural Studies (14 citations). Lanbo She has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Joyce Chai, Rui Fang, Changsong Liu, Yunyi Jia, Ning Xi, Yu Cheng, Yu Cheng, Kenneth Hanson, J. Bao and Nenghai Yu. Their work appears in journals such as AI Magazine, Annual Meeting of the Special Interest Group on Discourse and Dialogue, The HKU Scholars Hub (University of Hong Kong) and IFAC Proceedings Volumes.
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.