Quanwang Wu

2.4k total citations
64 papers, 1.7k citations indexed

About

Quanwang Wu is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Quanwang Wu has authored 64 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Artificial Intelligence, 35 papers in Information Systems and 25 papers in Computer Networks and Communications. Recurrent topics in Quanwang Wu's work include Cloud Computing and Resource Management (16 papers), IoT and Edge/Fog Computing (13 papers) and Machine Learning and Data Classification (11 papers). Quanwang Wu is often cited by papers focused on Cloud Computing and Resource Management (16 papers), IoT and Edge/Fog Computing (13 papers) and Machine Learning and Data Classification (11 papers). Quanwang Wu collaborates with scholars based in China, United States and Japan. Quanwang Wu's co-authors include Qingsheng Zhu, Dongdong Cheng, Yunni Xia, Junhao Wen, Jinlong Huang, Lijun Yang, MengChu Zhou, Fuyuki Ishikawa, Junnan Li and Dong-Hoon Shin and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Pattern Recognition.

In The Last Decade

Quanwang Wu

62 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Quanwang Wu China 24 879 731 659 312 139 64 1.7k
Ming‐Chao Chiang Taiwan 16 436 0.5× 337 0.5× 541 0.8× 269 0.9× 157 1.1× 83 1.3k
Renyu Yang China 22 681 0.8× 802 1.1× 945 1.4× 256 0.8× 126 0.9× 66 1.8k
Ligang He United Kingdom 24 510 0.6× 913 1.2× 1.2k 1.8× 291 0.9× 178 1.3× 163 1.9k
Hamid Beigy Iran 24 1.0k 1.2× 297 0.4× 693 1.1× 161 0.5× 267 1.9× 121 1.8k
Benjamin Moseley United States 15 594 0.7× 326 0.4× 611 0.9× 278 0.9× 79 0.6× 89 1.3k
Zhenjie Zhang China 26 1.1k 1.3× 565 0.8× 695 1.1× 191 0.6× 117 0.8× 100 2.2k
Asma Belhadi Norway 24 783 0.9× 460 0.6× 346 0.5× 192 0.6× 115 0.8× 76 1.5k
Dongxiao Yu China 27 838 1.0× 518 0.7× 1.5k 2.2× 355 1.1× 712 5.1× 230 2.7k
Fei Xue China 17 709 0.8× 741 1.0× 749 1.1× 310 1.0× 196 1.4× 65 1.9k
Suyel Namasudra India 30 901 1.0× 1.2k 1.6× 815 1.2× 399 1.3× 167 1.2× 87 2.3k

Countries citing papers authored by Quanwang Wu

Since Specialization
Citations

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

Fields of papers citing papers by Quanwang Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Quanwang Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Quanwang Wu. A scholar is included among the top collaborators of Quanwang Wu 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 Quanwang Wu. Quanwang Wu 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.
Wu, Quanwang, et al.. (2026). Efficient workflow offloading in private clouds using serverless computing. Expert Systems with Applications. 312. 131460–131460.
2.
Wu, Quanwang, et al.. (2025). Dynamically Scheduling Deadline-Constrained Interleaved Workflows on Heterogeneous Computing Systems. IEEE Transactions on Services Computing. 18(2). 758–769. 2 indexed citations
3.
Wu, Quanwang, et al.. (2025). Contention-aware workflow scheduling on heterogeneous computing systems with shared buses. Journal of Systems Architecture. 165. 103434–103434. 1 indexed citations
4.
Wu, Quanwang, et al.. (2024). A diversity and reliability-enhanced synthetic minority oversampling technique for multi-label learning. Information Sciences. 690. 121579–121579. 1 indexed citations
5.
Lu, Jianyun, et al.. (2024). HFS-CSR: A hierarchical feature selection method based on correlation and structural redundancy. Expert Systems with Applications. 262. 125660–125660. 2 indexed citations
6.
Wu, Quanwang, et al.. (2024). A Communication-Contention-Aware Privacy-Preserving Workflow Scheduling Method for Geo-Distributed Datacenters. IEEE Transactions on Services Computing. 17(5). 1887–1898. 2 indexed citations
7.
Wu, Quanwang, et al.. (2023). A co-training method based on parameter-free and single-step unlabeled data selection strategy with natural neighbors. International Journal of Machine Learning and Cybernetics. 14(8). 2887–2902. 2 indexed citations
8.
Wu, Quanwang, et al.. (2023). A Communication Contention-Cognizant Scheduling Approach for Workflow Execution Across Public and Private Clouds. IEEE Transactions on Automation Science and Engineering. 21(4). 7040–7051. 2 indexed citations
9.
Yu, Teng, Fengji Luo, Quanwang Wu, & Gianluca Ranzi. (2023). Blockchain in Smart Grids: A Review of Recent Developments. 23–59. 2 indexed citations
10.
Wang, Weiguo, et al.. (2023). A probabilistic modeling and evolutionary optimization approach for serverless workflow configuration. Software Practice and Experience. 54(9). 1697–1713. 5 indexed citations
11.
Wu, Quanwang, et al.. (2023). SIVLC: improving the performance of co-training by sufficient-irrelevant views and label consistency. Applied Intelligence. 53(18). 20710–20729. 2 indexed citations
12.
Wu, Quanwang, et al.. (2022). LAGAM: A Length-Adaptive Genetic Algorithm With Markov Blanket for High-Dimensional Feature Selection in Classification. IEEE Transactions on Cybernetics. 53(11). 6858–6869. 25 indexed citations
13.
Wu, Quanwang, et al.. (2022). A New Density Clustering Method based on Dynamic Local Density. 1–6. 1 indexed citations
14.
Wu, Quanwang, MengChu Zhou, & Junhao Wen. (2021). Endpoint Communication Contention-Aware Cloud Workflow Scheduling. IEEE Transactions on Automation Science and Engineering. 19(2). 1137–1150. 31 indexed citations
15.
Wu, Quanwang, MengChu Zhou, Qingsheng Zhu, Yunni Xia, & Junhao Wen. (2019). MOELS: Multiobjective Evolutionary List Scheduling for Cloud Workflows. IEEE Transactions on Automation Science and Engineering. 17(1). 166–176. 118 indexed citations
16.
Xia, Yunni, Qiang He, Yuandou Wang, et al.. (2018). A Fluctuation-Aware Approach for Predictive Web Service Composition. Swinburne Research Bank (Swinburne University of Technology). 121–128. 10 indexed citations
17.
Cheng, Dongdong, Qingsheng Zhu, Jinlong Huang, Quanwang Wu, & Lijun Yang. (2018). A Novel Cluster Validity Index Based on Local Cores. IEEE Transactions on Neural Networks and Learning Systems. 30(4). 985–999. 91 indexed citations
18.
Wu, Quanwang, Fuyuki Ishikawa, Qingsheng Zhu, & Yunni Xia. (2016). Energy and Migration Cost-Aware Dynamic Virtual Machine Consolidation in Heterogeneous Cloud Datacenters. IEEE Transactions on Services Computing. 12(4). 550–563. 96 indexed citations
19.
Wu, Quanwang, et al.. (2014). Broker-based SLA-aware composite service provisioning. Journal of Systems and Software. 96. 194–201. 13 indexed citations
20.
Wu, Quanwang, Qingsheng Zhu, & Peng Li. (2012). A caching mechanism for QoS-aware service composition. Journal of Web Engineering. 11(2). 119–130. 8 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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