Lichuan Ma
Impact in
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- Mobile Crowdsensing and Crowdsourcing
- Health Informatics top 10%
Papers in
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- Privacy-Preserving Technologies in Data 9
- Anomaly Detection Techniques and Applications 3
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- IoT and Edge/Fog Computing 4
- Cognitive Radio Networks and Spectrum Sensing 3
- Co-authors
- Qingqi Pei (9 shared papers)Yong Xiang (3 shared papers)Haojin Zhu (5 shared papers)Qingqi Pei (4 shared papers)Xuefeng Liu (3 shared papers)Yan Meng (3 shared papers)Suguo Du (1 shared paper)Xuemin Shen (1 shared paper)
In The Last Decade
Lichuan Ma
19 papers receiving 464 citations
Lichuan Ma's Hit Papers
Peers
Comparison fields: 5 of 59
- Computer Science Applications 92
- Health Informatics 17
- Artificial Intelligence 279
- Computer Networks and Communications 158
- Information Systems 146
Countries citing papers authored by Lichuan Ma
This map shows the geographic impact of Lichuan Ma'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 Lichuan Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lichuan Ma more than expected).
Fields of papers citing papers by Lichuan Ma
This network shows the impact of papers produced by Lichuan Ma. 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 Lichuan Ma. The network helps show where Lichuan Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Lichuan Ma, 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 | A Federated Learning Based Privacy-Preserving Smart Healthcare System Hit paper breakdown → | 2021 | 179 |
| 2 | 2018 | 134 | |
| 3 | 2020 | 35 | |
| 4 | 2017 | 33 | |
| 5 | 2023 | 21 | |
| 6 | 2019 | 12 | |
| 7 | 2023 | 11 | |
| 8 | 2017 | 8 | |
| 9 | 2019 | 8 | |
| 10 | 2019 | 7 | |
| 11 | 2015 | 6 | |
| 12 | 2021 | 6 | |
| 13 | 2014 | 5 | |
| 14 | 2020 | 3 | |
| 15 | 2024 | 1 | |
| 16 | 2025 | 1 | |
| 17 | 2020 | 1 | |
| 18 | 2024 | 1 | |
| 19 | 2019 | 1 |
About Lichuan Ma
Lichuan Ma is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Sociology and Political Science and Computer Vision and Pattern Recognition, having authored 19 papers that have together received 473 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (9 papers), Blockchain Technology Applications and Security (6 papers), IoT and Edge/Fog Computing (4 papers), Privacy, Security, and Data Protection (4 papers), Anomaly Detection Techniques and Applications (3 papers), Mobile Crowdsensing and Crowdsourcing (3 papers), Cognitive Radio Networks and Spectrum Sensing (3 papers) and Advanced Steganography and Watermarking Techniques (2 papers). The work is most often cited by research in Computer Science Applications (92 citations), Health Informatics (17 citations), Artificial Intelligence (279 citations), Computer Networks and Communications (158 citations) and Information Systems (146 citations). Lichuan Ma has collaborated with scholars based in China, Australia and Canada. Frequent co-authors include Qingqi Pei, Yong Xiang, Haojin Zhu, Qingqi Pei, Xuefeng Liu, Yan Meng, Suguo Du, Xuemin Shen, Yang Xiang and Licheng Wang. Their work appears in journals such as China Communications, IEEE Transactions on Vehicular Technology, Journal of Network and Computer Applications, Big Data Mining and Analytics and IEEE Transactions on Services Computing.
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.