Mo Li
Impact in
- Neurology top 10%
- Brain Tumor Detection and Classification
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Infrared Thermography in Medicine
Papers in
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- Advanced Graph Neural Networks 5
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- Data Management and Algorithms 7
- Video Coding and Compression Technologies 5
- Co-authors
- Yudong Yao (2 shared papers)Junchang Xin (7 shared papers)Zhiqiong Wang (4 shared papers)Hao Zhang (1 shared paper)Huaxia Wang (1 shared paper)Hanyu Jiang (1 shared paper)Chen Li (2 shared papers)Tao Jiang (1 shared paper)
- Journals
- Knowledge-Based Systems (2 papers)IEEE Access (2 papers)Lecture notes in computer science (9 papers)Journal of X-Ray Science and Technology (1 paper)Agricultural Systems (1 paper)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Mo Li
27 papers receiving 496 citations
Peers
Comparison fields: 5 of 66
- Neurology 107
- Radiology, Nuclear Medicine and Imaging 222
- Artificial Intelligence 367
- Computer Vision and Pattern Recognition 158
- Health Information Management 31
Countries citing papers authored by Mo Li
This map shows the geographic impact of Mo 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 Mo Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mo Li more than expected).
Fields of papers citing papers by Mo Li
This network shows the impact of papers produced by Mo 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 Mo Li. The network helps show where Mo Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Mo 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 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 261 | |
| 2 | 2020 | 156 | |
| 3 | 2005 | 31 | |
| 4 | 2024 | 15 | |
| 5 | 2014 | 11 | |
| 6 | 2010 | 8 | |
| 7 | 2006 | 4 | |
| 8 | 2020 | 3 | |
| 9 | 2023 | 3 | |
| 10 | 2019 | 3 | |
| 11 | 2019 | 3 | |
| 12 | 2006 | 3 | |
| 13 | 2006 | 3 | |
| 14 | 2023 | 2 | |
| 15 | 2024 | 2 | |
| 16 | 2018 | 2 | |
| 17 | 2024 | 1 | |
| 18 | Application of web-based data mining technology in digital libraries | 2007 | 1 |
| 19 | 2022 | 1 | |
| 20 | 2022 | 1 |
About Mo Li
Mo Li is a scholar working on Artificial Intelligence, Signal Processing, Computer Networks and Communications, Computer Vision and Pattern Recognition and Information Systems, having authored 35 papers that have together received 523 indexed citations. Recurring topics across this work include Data Management and Algorithms (7 papers), Caching and Content Delivery (7 papers), Video Coding and Compression Technologies (5 papers), Advanced Graph Neural Networks (5 papers), Opportunistic and Delay-Tolerant Networks (4 papers), Image and Video Quality Assessment (4 papers), Complex Network Analysis Techniques (4 papers) and Advanced Data Compression Techniques (3 papers). The work is most often cited by research in Neurology (107 citations), Radiology, Nuclear Medicine and Imaging (222 citations), Artificial Intelligence (367 citations), Computer Vision and Pattern Recognition (158 citations) and Health Information Management (31 citations). Mo Li has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Yudong Yao, Junchang Xin, Zhiqiong Wang, Hao Zhang, Huaxia Wang, Hanyu Jiang, Chen Li, Tao Jiang, Shiliang Ai and Xiaoyan Li. Their work appears in journals such as Knowledge-Based Systems, IEEE Access, Lecture notes in computer science, Journal of X-Ray Science and Technology and Agricultural Systems.
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.