Xiang Su
Impact in
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- IoT and Edge/Fog Computing
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- Context-Aware Activity Recognition Systems
- Augmented Reality Applications
Papers in
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- IoT and Edge/Fog Computing 25
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- Context-Aware Activity Recognition Systems 14
- Augmented Reality Applications 14
- Co-authors
- Yuxue Yang (4 shared papers)Shuangliang Yao (4 shared papers)Jukka Riekki (26 shared papers)Sasu Tarkoma (18 shared papers)Oleksiy Mazhelis (1 shared paper)Julien Mineraud (1 shared paper)Pan Hui (12 shared papers)Xiaoli Liu (13 shared papers)
In The Last Decade
Xiang Su
79 papers receiving 1.6k citations
Xiang Su's Hit Papers
Peers
Comparison fields: 5 of 105
- Computer Networks and Communications 587
- Computer Vision and Pattern Recognition 341
- Economics and Econometrics 438
- Marketing 139
- Information Systems 303
Countries citing papers authored by Xiang Su
This map shows the geographic impact of Xiang Su'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 Xiang Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiang Su more than expected).
Fields of papers citing papers by Xiang Su
This network shows the impact of papers produced by Xiang Su. 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 Xiang Su. The network helps show where Xiang Su may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiang Su, 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 91 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Nexus between green finance, fintech, and high-quality economic development: Empirical evidence from China Hit paper breakdown → | 2021 | 351 |
| 2 | A gap analysis of Internet-of-Things platforms Hit paper breakdown → | 2016 | 286 |
| 3 | 2016 | 104 | |
| 4 | 2022 | 88 | |
| 5 | 2022 | 70 | |
| 6 | 2016 | 52 | |
| 7 | 2023 | 50 | |
| 8 | 2009 | 45 | |
| 9 | 2014 | 39 | |
| 10 | 2023 | 37 | |
| 11 | 2014 | 30 | |
| 12 | 2022 | 28 | |
| 13 | 2018 | 23 | |
| 14 | 2021 | 23 | |
| 15 | 2020 | 22 | |
| 16 | 2022 | 21 | |
| 17 | 2022 | 21 | |
| 18 | 2023 | 20 | |
| 19 | 2013 | 18 | |
| 20 | 2016 | 18 |
About Xiang Su
Xiang Su is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems and Economics and Econometrics, having authored 91 papers that have together received 1.7k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (25 papers), Context-Aware Activity Recognition Systems (14 papers), Augmented Reality Applications (14 papers), Energy, Environment, Economic Growth (9 papers), Semantic Web and Ontologies (7 papers), Privacy-Preserving Technologies in Data (7 papers), Interactive and Immersive Displays (6 papers) and Service-Oriented Architecture and Web Services (5 papers). The work is most often cited by research in Computer Networks and Communications (587 citations), Computer Vision and Pattern Recognition (341 citations), Economics and Econometrics (438 citations), Marketing (139 citations) and Information Systems (303 citations). Xiang Su has collaborated with scholars based in Finland, China and Norway. Frequent co-authors include Yuxue Yang, Shuangliang Yao, Jukka Riekki, Sasu Tarkoma, Oleksiy Mazhelis, Julien Mineraud, Pan Hui, Xiaoli Liu, Lik‐Hang Lee and Junlan Tan. Their work appears in journals such as IEEE Transactions on Mobile Computing, IEEE Network, Resources Policy, Computer and IEEE Communications Magazine.
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.