Kewei Sha
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- IoT and Edge/Fog Computing 16
- Energy Efficient Wireless Sensor Networks 16
- Mobile Ad Hoc Networks 6
- Information Systems top 2%
- Cloud Data Security Solutions 9
- User Authentication and Security Systems 6
- Signal Processing top 5%
- Artificial Intelligence top 5%
- Privacy-Preserving Technologies in Data 8
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- Vehicular Ad Hoc Networks (VANETs) 7
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- Context-Aware Activity Recognition Systems 10
- Co-authors
- Weisong ShiT. Andrew YangWei WeiSadegh DavariZhiwei WangLoren SchwiebertYong XiJunzhao Du
- Journals
- IEEE Internet of Things Journal (3 papers)IEEE Transactions on Services Computing (2 papers)Wireless Personal Communications (2 papers)
- Partner nations
- United StatesChinaEstonia
In The Last Decade
Kewei Sha
66 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 83
- Computer Networks and Communications 938
- Information Systems 324
- Signal Processing 148
- Artificial Intelligence 316
- Electrical and Electronic Engineering 474
Countries citing papers authored by Kewei Sha
This map shows the geographic impact of Kewei Sha'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 Kewei Sha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kewei Sha more than expected).
Fields of papers citing papers by Kewei Sha
This network shows the impact of papers produced by Kewei Sha. 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 Kewei Sha. The network helps show where Kewei Sha may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kewei Sha, 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 | 2024 | 0 | |
| 2 | 2024 | 3 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 8 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 7 | |
| 7 | 2023 | 4 | |
| 8 | 2023 | 6 | |
| 9 | 2023 | 2 | |
| 10 | 2022 | 11 | |
| 11 | 2022 | 1 | |
| 12 | 2022 | 1 | |
| 13 | Governance Attributes of Consortium Blockchain Applications. | 2021 | 1 |
| 14 | 2021 | 14 | |
| 15 | 2019 | 23 | |
| 16 | 2017 | 10 | |
| 17 | 2010 | 3 | |
| 18 | 2010 | 19 | |
| 19 | 2007 | 5 | |
| 20 | 2004 | 2 |
About Kewei Sha
Kewei Sha is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Information Systems, Artificial Intelligence and Computer Science Applications, having authored 70 papers that have together received 1.3k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (16 papers), Energy Efficient Wireless Sensor Networks (16 papers), Context-Aware Activity Recognition Systems (10 papers), Cloud Data Security Solutions (9 papers), Privacy-Preserving Technologies in Data (8 papers), Vehicular Ad Hoc Networks (VANETs) (7 papers), User Authentication and Security Systems (6 papers) and Mobile Ad Hoc Networks (6 papers). The work is most often cited by research in Computer Networks and Communications (938 citations), Information Systems (324 citations), Signal Processing (148 citations), Artificial Intelligence (316 citations) and Electrical and Electronic Engineering (474 citations). Kewei Sha has collaborated with scholars based in United States, China and Estonia. Frequent co-authors include Weisong Shi, T. Andrew Yang, Wei Wei, Wei Wei, Sadegh Davari, Zhiwei Wang, Loren Schwiebert, Yong Xi, Junzhao Du and Tao Zhang. Their work appears in journals such as IEEE Internet of Things Journal, IEEE Transactions on Services Computing, Wireless Personal Communications, IEEE Access and Journal of Data and Information Quality.
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.