Xiaohan Li
Impact in
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Topic Modeling
- Machine Learning in Healthcare
- Information Systems top 5%
- Recommender Systems and Techniques
Papers in
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- Topic Modeling 9
- Advanced Graph Neural Networks 9
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- Recommender Systems and Techniques 8
- Co-authors
- Philip S. Yu (9 shared papers)Zheng Liu (6 shared papers)Shu Wu (2 shared papers)Liang Wang (2 shared papers)Kannan Achan (6 shared papers)Yifan Zhang (3 shared papers)Jungang Jiang (3 shared papers)Lei Wang (3 shared papers)
- Journals
- Drones (2 papers)Nano Research (2 papers)Psychoneuroendocrinology (2 papers)The Science of The Total Environment (2 papers)Journal of Nanoscience and Nanotechnology (1 paper)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Xiaohan Li
65 papers receiving 706 citations
Peers
Comparison fields: 5 of 131
- Artificial Intelligence 228
- Information Systems 141
- Computer Vision and Pattern Recognition 116
- Metals and Alloys 11
- Health Information Management 16
Countries citing papers authored by Xiaohan Li
This map shows the geographic impact of Xiaohan Li'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 Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaohan Li more than expected).
Fields of papers citing papers by Xiaohan Li
This network shows the impact of papers produced by Xiaohan Li. 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 Li. The network helps show where Xiaohan Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaohan Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 74 | |
| 2 | 2020 | 56 | |
| 3 | 2022 | 50 | |
| 4 | 2017 | 45 | |
| 5 | 2020 | 41 | |
| 6 | 2020 | 40 | |
| 7 | 2024 | 26 | |
| 8 | 2023 | 25 | |
| 9 | 2020 | 24 | |
| 10 | 2022 | 23 | |
| 11 | 2022 | 20 | |
| 12 | 2023 | 18 | |
| 13 | 2021 | 17 | |
| 14 | 2017 | 16 | |
| 15 | 2021 | 14 | |
| 16 | 2021 | 14 | |
| 17 | 2019 | 13 | |
| 18 | 2018 | 13 | |
| 19 | 2021 | 12 | |
| 20 | 2022 | 12 |
About Xiaohan Li
Xiaohan Li is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Biomedical Engineering and Materials Chemistry, having authored 74 papers that have together received 719 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Advanced Graph Neural Networks (9 papers), Recommender Systems and Techniques (8 papers), Lignin and Wood Chemistry (4 papers), Advanced Vision and Imaging (4 papers), Robotics and Sensor-Based Localization (4 papers), Ionic liquids properties and applications (3 papers) and Optical measurement and interference techniques (3 papers). The work is most often cited by research in Artificial Intelligence (228 citations), Information Systems (141 citations), Computer Vision and Pattern Recognition (116 citations), Metals and Alloys (11 citations) and Health Information Management (16 citations). Xiaohan Li has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Philip S. Yu, Zheng Liu, Shu Wu, Liang Wang, Kannan Achan, Yifan Zhang, Jungang Jiang, Lei Wang, Stephen Guo and Shuaiyu Wang. Their work appears in journals such as Drones, Nano Research, Psychoneuroendocrinology, The Science of The Total Environment and Journal of Nanoscience and Nanotechnology.
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.