Xiaohan Lan
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
- Semantic Web and Ontologies
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- Multimodal Machine Learning Applications
- Video Analysis and Summarization
- Graph Theory and Algorithms
- Human Pose and Action Recognition
Papers in
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- Multimodal Machine Learning Applications 7
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- Advanced Graph Neural Networks 1
- Co-authors
- Yu Zhang (1 shared paper)Qingsong Lv (1 shared paper)Zhichun Wang (1 shared paper)Wenwu Zhu (7 shared papers)Xin Wang (5 shared papers)Yitian Yuan (4 shared papers)Zhi Wang (3 shared papers)Long Chen (2 shared papers)
- Journals
- ACM Transactions on Multimedia Computing Communications and Applications (2 papers)arXiv (Cornell University) (1 paper)ACM International Conference on Multimedia (ACM MM) (3 papers)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)Conference on Empirical Methods in Natural Language Processing (EMNLP) (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Xiaohan Lan
8 papers receiving 561 citations
Xiaohan Lan's Hit Papers
Peers
Comparison fields: 5 of 27
- Artificial Intelligence 414
- Computer Vision and Pattern Recognition 161
- Management Science and Operations Research 16
- Signal Processing 6
- Information Systems 14
Countries citing papers authored by Xiaohan Lan
This map shows the geographic impact of Xiaohan Lan'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 Xiaohan Lan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaohan Lan more than expected).
Fields of papers citing papers by Xiaohan Lan
This network shows the impact of papers produced by Xiaohan Lan. 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 Xiaohan Lan. The network helps show where Xiaohan Lan may publish in the future.
Co-authors
The 15 scholars most cited alongside Xiaohan Lan, 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 | Cross-lingual Knowledge Graph Alignment via Graph Convolutional Networks Hit paper breakdown → | 2018 | 437 |
| 2 | 2021 | 47 | |
| 3 | 2022 | 33 | |
| 4 | 2023 | 16 | |
| 5 | 2022 | 15 | |
| 6 | 2023 | 10 | |
| 7 | 2023 | 8 | |
| 8 | 2022 | 3 |
About Xiaohan Lan
Xiaohan Lan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Nuclear Energy and Engineering, Waste Management and Disposal and Infectious Diseases, having authored 8 papers that have together received 569 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (7 papers) and Advanced Graph Neural Networks (1 paper). The work is most often cited by research in Artificial Intelligence (414 citations), Computer Vision and Pattern Recognition (161 citations), Management Science and Operations Research (16 citations), Signal Processing (6 citations) and Information Systems (14 citations). Xiaohan Lan has collaborated with scholars based in China and United States. Frequent co-authors include Yu Zhang, Qingsong Lv, Zhichun Wang, Wenwu Zhu, Xin Wang, Yitian Yuan, Zhi Wang, Long Chen, Zhi Wang and Hong Chen. Their work appears in journals such as ACM Transactions on Multimedia Computing Communications and Applications, arXiv (Cornell University), ACM International Conference on Multimedia (ACM MM), Proceedings of the AAAI Conference on Artificial Intelligence and Conference on Empirical Methods in Natural Language Processing (EMNLP).
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.