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 28
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- Context-Aware Activity Recognition Systems 20
- Augmented Reality Applications 14
- Co-authors
- Yuxue Yang (4 shared papers)Shuangliang Yao (4 shared papers)Jukka Riekki (33 shared papers)Sasu Tarkoma (20 shared papers)Oleksiy Mazhelis (1 shared paper)Julien Mineraud (1 shared paper)Xiaoli Liu (16 shared papers)Pan Hui (13 shared papers)
In The Last Decade
Xiang Su
89 papers receiving 1.8k citations
Xiang Su's Hit Papers
Peers
Comparison fields: 5 of 109
- Computer Networks and Communications 689
- Computer Vision and Pattern Recognition 392
- Economics and Econometrics 444
- Marketing 144
- Information Systems 356
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 103 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 | 359 |
| 2 | A gap analysis of Internet-of-Things platforms Hit paper breakdown → | 2016 | 342 |
| 3 | 2016 | 119 | |
| 4 | 2022 | 94 | |
| 5 | 2022 | 70 | |
| 6 | 2016 | 59 | |
| 7 | 2023 | 54 | |
| 8 | 2009 | 46 | |
| 9 | 2014 | 43 | |
| 10 | 2023 | 40 | |
| 11 | 2014 | 37 | |
| 12 | 2022 | 28 | |
| 13 | 2020 | 27 | |
| 14 | 2018 | 26 | |
| 15 | 2021 | 24 | |
| 16 | 2022 | 21 | |
| 17 | 2013 | 21 | |
| 18 | 2023 | 21 | |
| 19 | 2022 | 21 | |
| 20 | 2014 | 19 |
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 103 papers that have together received 1.9k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (28 papers), Context-Aware Activity Recognition Systems (20 papers), Augmented Reality Applications (14 papers), Privacy-Preserving Technologies in Data (9 papers), Energy, Environment, Economic Growth (9 papers), Semantic Web and Ontologies (9 papers), Service-Oriented Architecture and Web Services (6 papers) and Interactive and Immersive Displays (6 papers). The work is most often cited by research in Computer Networks and Communications (689 citations), Computer Vision and Pattern Recognition (392 citations), Economics and Econometrics (444 citations), Marketing (144 citations) and Information Systems (356 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, Xiaoli Liu, Pan Hui, Lik‐Hang Lee and Rong Wang. Their work appears in journals such as IEEE Transactions on Mobile Computing, Resources Policy, IEEE Network, 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.