Dapeng Wu

20.9k total citations · 4 hit papers
524 papers, 14.6k citations indexed

About

Dapeng Wu is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Dapeng Wu has authored 524 papers receiving a total of 14.6k indexed citations (citations by other indexed papers that have themselves been cited), including 253 papers in Computer Networks and Communications, 202 papers in Electrical and Electronic Engineering and 147 papers in Computer Vision and Pattern Recognition. Recurrent topics in Dapeng Wu's work include Cooperative Communication and Network Coding (69 papers), Advanced Wireless Network Optimization (60 papers) and Advanced MIMO Systems Optimization (59 papers). Dapeng Wu is often cited by papers focused on Cooperative Communication and Network Coding (69 papers), Advanced Wireless Network Optimization (60 papers) and Advanced MIMO Systems Optimization (59 papers). Dapeng Wu collaborates with scholars based in United States, China and Hong Kong. Dapeng Wu's co-authors include Rohit Negi, Tie Qiu, Xianbin Cao, Zhenyu Xiao, Yonggang Wen, Weiwen Zhang, Pan Zhou, Lipeng Zhu, Yuguang Fang and Peng Yang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and ACS Nano.

In The Last Decade

Dapeng Wu

493 papers receiving 14.1k citations

Hit Papers

Effective capacity: A wir... 2003 2026 2010 2018 2003 2013 2020 2018 250 500 750 1000

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Dapeng Wu 8.0k 6.5k 2.9k 2.2k 1.9k 524 14.6k
Shiwen Mao 7.9k 1.0× 9.3k 1.4× 2.1k 0.7× 3.1k 1.4× 2.0k 1.0× 498 17.3k
Qian Zhang 10.7k 1.3× 8.4k 1.3× 2.7k 0.9× 2.0k 0.9× 862 0.4× 893 17.9k
K. J. Ray Liu 9.4k 1.2× 10.4k 1.6× 2.3k 0.8× 1.5k 0.7× 1.3k 0.7× 500 17.0k
Mianxiong Dong 8.0k 1.0× 5.2k 0.8× 1.8k 0.6× 3.0k 1.4× 1.4k 0.7× 486 14.0k
Nirwan Ansari 9.9k 1.2× 9.6k 1.5× 3.7k 1.3× 2.8k 1.3× 2.5k 1.3× 632 19.2k
Tarik Taleb 13.9k 1.7× 7.5k 1.2× 1.9k 0.6× 1.9k 0.9× 2.8k 1.4× 440 17.9k
Yu Wang 6.6k 0.8× 4.8k 0.7× 2.0k 0.7× 2.3k 1.1× 759 0.4× 633 13.6k
Lionel M. Ni 10.7k 1.3× 10.6k 1.6× 3.5k 1.2× 2.8k 1.3× 1.5k 0.8× 450 22.0k
Kaoru Ota 6.6k 0.8× 4.1k 0.6× 1.5k 0.5× 2.5k 1.1× 1.1k 0.6× 360 11.5k
Hsiao‐Hwa Chen 10.1k 1.3× 10.8k 1.7× 1.1k 0.4× 2.2k 1.0× 1.3k 0.7× 485 15.8k

Countries citing papers authored by Dapeng Wu

Since Specialization
Citations

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

Fields of papers citing papers by Dapeng Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dapeng Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Dapeng Wu. A scholar is included among the top collaborators of Dapeng 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 Dapeng Wu. Dapeng 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.
Chen, Zhengchuan, Xin Gao, Jing Wang, et al.. (2025). Optimization of Weighted Energy Efficiency for RSMA-RIS-Assisted ISAC System. IEEE Transactions on Vehicular Technology. 74(11). 18249–18254.
2.
Qian, Feng, et al.. (2025). DeMo: Experiences of Deploying a Large-Scale Indoor Delivery Monitoring System. IEEE Transactions on Mobile Computing. 24(12). 13015–13033.
3.
Ye, Yuxiao, et al.. (2025). AoI-Aware Air-Ground Mobile Crowdsensing by Multi-Agent Curriculum Learning With Collaborative Observation Augmentation. IEEE Transactions on Mobile Computing. 24(11). 11675–11687. 1 indexed citations
4.
5.
Chen, Zhengchuan, et al.. (2024). Modern Random Access-Based IoT Networks Design: From a Timeliness-Fidelity Perspective. IEEE Communications Magazine. 62(7). 74–80. 3 indexed citations
6.
Zhao, Qiran, et al.. (2024). Indoor Periodic Fingerprint Collections by Vehicular Crowdsensing via Primal-Dual Multi-Agent Deep Reinforcement Learning. IEEE Journal on Selected Areas in Communications. 42(10). 2625–2641. 1 indexed citations
7.
Chen, Ning, et al.. (2024). A Distributed Co-Evolutionary Optimization Method With Motif for Large-Scale IoT Robustness. IEEE/ACM Transactions on Networking. 32(5). 4085–4098. 16 indexed citations
8.
Zhou, Xiaobo, et al.. (2024). Quantum-Inspired Robust Networking Model With Multiverse Co-Evolution for Scale-Free IoT. IEEE Transactions on Mobile Computing. 23(12). 14085–14098. 4 indexed citations
10.
Chen, Zhengchuan, et al.. (2023). Coded Slotted ALOHA Scheme With Multi-Packet Reception Under Erasure Channels. IEEE Transactions on Vehicular Technology. 72(12). 15804–15818. 1 indexed citations
11.
Gao, Yue, et al.. (2023). How to Allocate Resources in Cloud-Native Networks Towards 6G. IEEE Network. 38(2). 240–246. 7 indexed citations
12.
Chen, Chen, Cong Wang, Tie Qiu, Mohammed Atiquzzaman, & Dapeng Wu. (2020). Caching in Vehicular Named Data Networking: Architecture, Schemes and Future Directions. IEEE Communications Surveys & Tutorials. 22(4). 2378–2407. 103 indexed citations
13.
Wang, Kehao, et al.. (2020). Reversible Data Hiding Based on Structural Similarity Block Selection. IEEE Access. 8. 20375–20385. 6 indexed citations
14.
Liu, Chi Harold, Chengzhe Piao, Zipeng Dai, et al.. (2020). Time-Aware Location Prediction by Convolutional Area-of-Interest Modeling and Memory-Augmented Attentive LSTM. IEEE Transactions on Knowledge and Data Engineering. 34(5). 2472–2484. 19 indexed citations
15.
Qiu, Tie, Jiancheng Chi, Xiaobo Zhou, et al.. (2020). Edge Computing in Industrial Internet of Things: Architecture, Advances and Challenges. IEEE Communications Surveys & Tutorials. 22(4). 2462–2488. 497 indexed citations breakdown →
16.
Liu, Chi Harold, Zipeng Dai, Yinuo Zhao, et al.. (2019). Distributed and Energy-Efficient Mobile Crowdsensing with Charging Stations by Deep Reinforcement Learning. IEEE Transactions on Mobile Computing. 20(1). 130–146. 94 indexed citations
17.
Zhu, Lipeng, Jun Zhang, Zhenyu Xiao, et al.. (2019). 3-D Beamforming for Flexible Coverage in Millimeter-Wave UAV Communications. IEEE Wireless Communications Letters. 8(3). 837–840. 130 indexed citations
18.
Yang, Peng, Xianbin Cao, Xing Xi, Zhenyu Xiao, & Dapeng Wu. (2018). Three-Dimensional Drone-Cell Deployment for Congestion Mitigation in Cellular Networks. IEEE Transactions on Vehicular Technology. 67(10). 9867–9881. 26 indexed citations
19.
Li, Yumeng, Wenbo Du, Peng Yang, et al.. (2018). A Satisficing Conflict Resolution Approach for Multiple UAVs. IEEE Internet of Things Journal. 6(2). 1866–1878. 48 indexed citations
20.
Zhang, Xu, Hao Yin, Dapeng Wu, et al.. (2017). SSL: ASurrogate-Based Method for Large-ScaleStatisticalLatencyMeasurement. IEEE Transactions on Services Computing. 13(5). 958–968. 14 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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