Lianyong Qi

2.8k total citations
61 papers, 1.9k citations indexed

About

Lianyong Qi is a scholar working on Computer Networks and Communications, Artificial Intelligence and Information Systems. According to data from OpenAlex, Lianyong Qi has authored 61 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computer Networks and Communications, 28 papers in Artificial Intelligence and 24 papers in Information Systems. Recurrent topics in Lianyong Qi's work include IoT and Edge/Fog Computing (14 papers), Recommender Systems and Techniques (13 papers) and Caching and Content Delivery (11 papers). Lianyong Qi is often cited by papers focused on IoT and Edge/Fog Computing (14 papers), Recommender Systems and Techniques (13 papers) and Caching and Content Delivery (11 papers). Lianyong Qi collaborates with scholars based in China, Australia and Japan. Lianyong Qi's co-authors include Xiaolong Xu, Fan Wang, Mohammad R. Khosravi, Yuwen Liu, Xiaokang Zhou, Yihong Yang, Wanchun Dou, Wajid Rafique, Shancang Li and Huaizhen Kou and has published in prestigious journals such as Information Sciences, IEEE Transactions on Industrial Informatics and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Lianyong Qi

58 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lianyong Qi China 24 784 630 606 330 254 61 1.9k
Fei Hao China 26 853 1.1× 534 0.8× 464 0.8× 258 0.8× 151 0.6× 167 2.2k
Yueshen Xu China 25 665 0.8× 907 1.4× 1.0k 1.7× 383 1.2× 368 1.4× 72 2.2k
Aiiad Albeshri Saudi Arabia 26 743 0.9× 583 0.9× 921 1.5× 303 0.9× 243 1.0× 92 2.3k
Qianmu Li China 27 1.0k 1.3× 902 1.4× 919 1.5× 364 1.1× 299 1.2× 222 2.5k
Yuyu Yin China 27 817 1.0× 1.1k 1.8× 1.1k 1.8× 434 1.3× 373 1.5× 117 2.5k
Kostas Kolomvatsos Greece 16 434 0.6× 557 0.9× 547 0.9× 235 0.7× 134 0.5× 106 1.4k
Stathes Hadjiefthymiades Greece 22 526 0.7× 604 1.0× 993 1.6× 567 1.7× 412 1.6× 179 2.2k
Zhiqiu Huang China 23 749 1.0× 999 1.6× 424 0.7× 166 0.5× 171 0.7× 241 2.1k
Fan Liang United States 16 589 0.8× 766 1.2× 1.2k 2.0× 260 0.8× 464 1.8× 46 2.2k
Iyad Katib Saudi Arabia 24 583 0.7× 392 0.6× 800 1.3× 229 0.7× 562 2.2× 106 2.3k

Countries citing papers authored by Lianyong Qi

Since Specialization
Citations

This map shows the geographic impact of Lianyong Qi'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 Lianyong Qi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lianyong Qi more than expected).

Fields of papers citing papers by Lianyong Qi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lianyong Qi. 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 Lianyong Qi. The network helps show where Lianyong Qi may publish in the future.

Co-authorship network of co-authors of Lianyong Qi

This figure shows the co-authorship network connecting the top 25 collaborators of Lianyong Qi. A scholar is included among the top collaborators of Lianyong Qi 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 Lianyong Qi. Lianyong Qi 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.
Hu, Xiyuan, Lianyong Qi, Xiaolong Xu, et al.. (2025). Deep Learning to Hash for Time-Aware QoS Prediction Based on VQ-VAE. IEEE Transactions on Services Computing. 18(5). 2726–2739.
2.
Cui, Guangming, et al.. (2025). CADEC: A Combinatorial Auction for Dynamic Distributed DNN Inference Scheduling in Edge-Cloud Networks. IEEE Transactions on Mobile Computing. 24(10). 10024–10041. 1 indexed citations
3.
Qi, Lianyong, Victor S. Sheng, Xiaolong Xu, & Jinjun Chen. (2024). Special Issue on “Ensuring security for artificial intelligence applications in mobile edge computing software systems”. Software Practice and Experience. 54(9). 1593–1595. 1 indexed citations
4.
Qi, Lianyong, et al.. (2023). An accuracy-enhanced group recommendation approach based on DEMATEL. Pattern Recognition Letters. 167. 171–180. 14 indexed citations
5.
Liu, Yuwen, et al.. (2023). A Novel Short-Term Traffic Prediction Model Based on SVD and ARIMA With Blockchain in Industrial Internet of Things. IEEE Internet of Things Journal. 10(24). 21217–21226. 41 indexed citations
6.
Zhou, Xiaokang, Wei Liang, Kevin I‐Kai Wang, et al.. (2023). Information Theoretic Learning-Enhanced Dual-Generative Adversarial Networks With Causal Representation for Robust OOD Generalization. IEEE Transactions on Neural Networks and Learning Systems. 36(2). 2066–2079. 64 indexed citations
7.
Feng, Zhiyong, Xian Zhou, Hongyue Wu, et al.. (2023). Attention-based neural networks for trust evaluation in online social networks. Information Sciences. 630. 507–522. 12 indexed citations
8.
Kou, Huaizhen, et al.. (2023). Diversity-driven automated web API recommendation based on implicit requirements. Applied Soft Computing. 136. 110137–110137. 10 indexed citations
9.
Shen, Yue, et al.. (2023). A game theory-based COVID-19 close contact detecting method with edge computing collaboration. Computer Communications. 207. 36–45. 2 indexed citations
10.
Dou, Wanchun, et al.. (2022). SeeMe: An intelligent edge server selection method for location‐aware business task computing over IIoT. Software Practice and Experience. 54(10). 1939–1956.
11.
12.
Yang, Yihong, Xuan Yang, Mohsen Heidari, et al.. (2022). ASTREAM: Data-Stream-Driven Scalable Anomaly Detection With Accuracy Guarantee in IIoT Environment. IEEE Transactions on Network Science and Engineering. 10(5). 3007–3016. 64 indexed citations
13.
Dai, Haipeng, Meng Li, Wei Wang, et al.. (2022). Bloom Filter with Noisy Coding Framework for Multi-Set Membership Testing. IEEE Transactions on Knowledge and Data Engineering. 1–14. 54 indexed citations
14.
Dou, Wanchun, et al.. (2022). Architecture of virtual edge data center with intelligent metadata service of a geo-distributed file system. Journal of Systems Architecture. 128. 102545–102545. 7 indexed citations
15.
Zhou, Zhili, Yulan Zhang, Zhihua Xia, et al.. (2021). Coverless Information Hiding Based on Probability Graph Learning for Secure Communication in IoT Environment. IEEE Internet of Things Journal. 9(12). 9332–9341. 20 indexed citations
16.
Wang, Yingjie, et al.. (2020). Walrasian Equilibrium-Based Multiobjective Optimization for Task Allocation in Mobile Crowdsourcing. IEEE Transactions on Computational Social Systems. 7(4). 1033–1046. 72 indexed citations
17.
Liu, Hanwen, Huaizhen Kou, Chao Yan, & Lianyong Qi. (2020). Keywords-Driven and Popularity-Aware Paper Recommendation Based on Undirected Paper Citation Graph. Complexity. 2020. 1–15. 53 indexed citations
18.
Kou, Huaizhen, Hanwen Liu, Yucong Duan, et al.. (2020). Building trust/distrust relationships on signed social service network through privacy-aware link prediction process. Applied Soft Computing. 100. 106942–106942. 70 indexed citations
19.
Tang, Wenjuan, et al.. (2020). Secure Information Transmissions in Wireless-Powered Cognitive Radio Networks for Internet of Medical Things. Security and Communication Networks. 2020. 1–10. 4 indexed citations
20.
Zhang, Xuyun, et al.. (2018). Collaborative Network Traffic Analysis via Alternating Direction Method of Multipliers. FedUni ResearchOnline (Federation University Australia). 547–552. 1 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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