Xiang Su

1.0k total citations · 1 hit paper
27 papers, 650 citations indexed

About

Xiang Su is a scholar working on Computer Networks and Communications, Artificial Intelligence and Information Systems. According to data from OpenAlex, Xiang Su has authored 27 papers receiving a total of 650 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Networks and Communications, 8 papers in Artificial Intelligence and 6 papers in Information Systems. Recurrent topics in Xiang Su's work include IoT and Edge/Fog Computing (6 papers), Cloud Computing and Resource Management (3 papers) and Privacy-Preserving Technologies in Data (3 papers). Xiang Su is often cited by papers focused on IoT and Edge/Fog Computing (6 papers), Cloud Computing and Resource Management (3 papers) and Privacy-Preserving Technologies in Data (3 papers). Xiang Su collaborates with scholars based in China, Finland and Hong Kong. Xiang Su's co-authors include Pan Hui, Yuanyuan Chen, Zhishuai Li, Yisheng Lv, Gang Xiong, Yonglin Tian, Pan Hui, Sasu Tarkoma, Yong Li and Tong Li and has published in prestigious journals such as Proceedings of the IEEE, IEEE Transactions on Vehicular Technology and IEEE Transactions on Intelligent Transportation Systems.

In The Last Decade

Xiang Su

24 papers receiving 635 citations

Hit Papers

A Multi-Stream Feature Fusion Approach for Traffic Predic... 2020 2026 2022 2024 2020 50 100 150 200

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Xiang Su China 9 213 123 115 109 99 27 650
Susanna Pirttikangas Finland 13 177 0.8× 167 1.4× 115 1.0× 135 1.2× 81 0.8× 71 607
Wanneng Shu China 15 357 1.7× 220 1.8× 176 1.5× 162 1.5× 81 0.8× 52 831
Quratulain Arshad Saudi Arabia 11 330 1.5× 147 1.2× 190 1.7× 147 1.3× 130 1.3× 17 844
Saleh M. Altowaijri Saudi Arabia 13 223 1.0× 97 0.8× 132 1.1× 112 1.0× 89 0.9× 32 592
Zhidan Liu China 14 107 0.5× 57 0.5× 119 1.0× 178 1.6× 75 0.8× 38 573
Chyi‐Ren Dow Taiwan 13 327 1.5× 105 0.9× 255 2.2× 88 0.8× 124 1.3× 95 858
Dongliang Chen China 9 193 0.9× 164 1.3× 88 0.8× 174 1.6× 67 0.7× 15 646
Ekaterina Gilman Finland 13 158 0.7× 101 0.8× 69 0.6× 96 0.9× 110 1.1× 37 444
Mingliang Hou China 14 149 0.7× 71 0.6× 103 0.9× 196 1.8× 83 0.8× 47 606
Husnu S. Narman United States 12 292 1.4× 194 1.6× 137 1.2× 126 1.2× 54 0.5× 60 675

Countries citing papers authored by Xiang Su

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Xiang Su

This figure shows the co-authorship network connecting the top 25 collaborators of Xiang Su. A scholar is included among the top collaborators of Xiang Su based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiang Su. Xiang Su is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Xu, Dianlei, Xiang Su, Gopika Premsankar, et al.. (2025). Dynamic Hierarchical Reinforcement Learning Framework for Energy-Efficient 5G Base Stations in Urban Environments. IEEE Transactions on Mobile Computing. 24(9). 8582–8599. 2 indexed citations
2.
Li, Changqing, et al.. (2024). UAV Swarm Centroid Tracking for Edge Computing Applications Using GRU-Assisted Multi-Model Filtering. Electronics. 13(6). 1054–1054. 1 indexed citations
3.
Su, Xiang, et al.. (2024). A Survey on Model-heterogeneous Federated Learning: Problems, Methods, and Prospects. 7725–7734. 3 indexed citations
4.
Su, Xiang, et al.. (2023). Data Augmented of Mechanical Fault Sound Signal based on Generative Adversarial Networks. Periodica Polytechnica Electrical Engineering and Computer Science. 68(1). 74–93.
5.
Su, Xiang, et al.. (2022). EmgAuth: Unlocking Smartphones with EMG Signals. IEEE Transactions on Mobile Computing. 1–1. 4 indexed citations
6.
Xu, Dianlei, Tong Li, Yong Li, et al.. (2021). Edge Intelligence: Empowering Intelligence to the Edge of Network. Proceedings of the IEEE. 109(11). 1778–1837. 139 indexed citations
7.
Su, Xiang, Xiaoli Liu, Naser Hossein Motlagh, et al.. (2021). Intelligent and Scalable Air Quality Monitoring With 5G Edge. IEEE Internet Computing. 25(2). 35–44. 26 indexed citations
8.
Alhilal, Ahmad, et al.. (2021). CAD3: Edge-facilitated Real-time Collaborative Abnormal Driving Distributed Detection. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 718–728. 3 indexed citations
9.
Li, Yuhong, Di Jin, Bailin Wang, et al.. (2020). Predicting Internet of Things Data Traffic Through LSTM and Autoregressive Spectrum Analysis. Työväentutkimus Vuosikirja. 1–8. 5 indexed citations
10.
Li, Zhishuai, Gang Xiong, Yonglin Tian, et al.. (2020). A Multi-Stream Feature Fusion Approach for Traffic Prediction. IEEE Transactions on Intelligent Transportation Systems. 23(2). 1456–1466. 221 indexed citations breakdown →
11.
Liu, Xuefeng, et al.. (2020). EmgAuth: An EMG-based Smartphone Unlocking System Using Siamese Network. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1–10. 20 indexed citations
12.
Chen, Shichao, et al.. (2019). Research and Application of Big Data Fusion Management Platform in Petroleum Industry. 6 22. 2108–2113. 1 indexed citations
13.
Lee, Lik‐Hang, Kit Yung Lam, Tong Li, et al.. (2019). Quadmetric Optimized Thumb-to-Finger Interaction for Force Assisted One-Handed Text Entry on Mobile Headsets. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 3(3). 1–27. 31 indexed citations
14.
Wang, Zhiying, Nianxin Wang, Xiang Su, & Shilun Ge. (2019). An empirical study on business analytics affordances enhancing the management of cloud computing data security. International Journal of Information Management. 50. 387–394. 87 indexed citations
15.
Flores, Huber, Pan Hui, Petteri Nurmi, et al.. (2017). Evidence-Aware Mobile Computational Offloading. IEEE Transactions on Mobile Computing. 17(8). 1834–1850. 38 indexed citations
16.
Flores, Huber, Xiang Su, Vassilis Kostakos, et al.. (2017). Large-scale offloading in the Internet of Things. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 479–484. 30 indexed citations
17.
Flores, Huber, Xiang Su, Vassilis Kostakos, et al.. (2017). Modeling Mobile Code Acceleration in the Cloud. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 557. 480–491. 3 indexed citations
18.
Su, Xiang, et al.. (2013). Design and Implementation of Logistics Intelligent Management and Control Systems for Steel Enterprises. Applied Mechanics and Materials. 380-384. 716–721. 1 indexed citations
19.
Su, Xiang. (2008). Research and Implementation of Embedded RFID Middleware System. Jisuanji gongcheng.
20.
Su, Xiang, et al.. (2005). Presentation of Programming Domain Knowledge with Ontology. 3 indexed citations

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.

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