Jun Wu

4.8k total citations · 3 hit papers
218 papers, 3.1k citations indexed

About

Jun Wu is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jun Wu has authored 218 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 95 papers in Electrical and Electronic Engineering, 69 papers in Computer Networks and Communications and 59 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jun Wu's work include Cooperative Communication and Network Coding (26 papers), Advanced MIMO Systems Optimization (22 papers) and Video Coding and Compression Technologies (19 papers). Jun Wu is often cited by papers focused on Cooperative Communication and Network Coding (26 papers), Advanced MIMO Systems Optimization (22 papers) and Video Coding and Compression Technologies (19 papers). Jun Wu collaborates with scholars based in China, United States and Australia. Jun Wu's co-authors include Lingxi Xie, Qi Tian, Xin Chen, Yonggang Wen, Zhifeng Zhang, Rui Wang, Hong Yu, Die Hu, Qingwen Liu and Pengfei Xia and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLANT PHYSIOLOGY and IEEE Transactions on Image Processing.

In The Last Decade

Jun Wu

203 papers receiving 3.1k citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Progressive Differentiable Architecture Search: Bridging the Depth Gap Between Search and Evaluation

2019 368 citations Jun Wu et al. profile →
Cloud radio access network (C-RAN): a primer

2015 342 citations Jun Wu et al. profile →
Personalized Federated Learning With Differential Privacy and Convergence Guarantee

2023 97 citations Kang Wei, Jun Li et al. IEEE Transactions on Information Forensics and Security profile →

Author Peers

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

Author						Papers	Cites
Jun Wu	1.4k	958	793	665	355	218	3.1k
Li Erran Li	1.3k 0.9×	2.0k 2.1×	1.0k 1.3×	457 0.7×	334 0.9×	63	3.5k
Vaneet Aggarwal	1.5k 1.1×	1.5k 1.6×	615 0.8×	631 0.9×	246 0.7×	251	3.6k
Zhongfeng Wang	1.9k 1.3×	1.1k 1.1×	795 1.0×	1.1k 1.7×	107 0.3×	352	3.4k
Zhen Yang	1.9k 1.3×	810 0.8×	366 0.5×	523 0.8×	461 1.3×	235	2.8k
Hong Wen	1.9k 1.3×	1.5k 1.6×	366 0.5×	949 1.4×	508 1.4×	219	3.5k
Jizhong Zhao	2.0k 1.4×	1.3k 1.4×	705 0.9×	467 0.7×	191 0.5×	158	3.5k
Carlo Fischione	2.8k 1.9×	2.5k 2.6×	432 0.5×	505 0.8×	398 1.1×	247	4.9k
Miroslav Vozňák	2.2k 1.5×	1.1k 1.2×	225 0.3×	858 1.3×	481 1.4×	396	3.8k
Gexiang Zhang	1.3k 0.9×	530 0.6×	393 0.5×	1.3k 2.0×	151 0.4×	225	4.7k
Zoran Salčić	954 0.7×	610 0.6×	460 0.6×	890 1.3×	376 1.1×	255	3.0k

Countries citing papers authored by Jun Wu

Since Specialization

Citations

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

Fields of papers citing papers by Jun Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Wu. A scholar is included among the top collaborators of Jun 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 Jun Wu. Jun Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Chen, Yankai, et al.. (2025). Rank Gap Sensitive Deep AUC maximization for CTR prediction. Pattern Recognition. 164. 111496–111496. 2 indexed citations

Wang, Tianying, Jun Wu, Cheng-Kui Li, et al.. (2025). Energy consumption analysis and performance evaluation of electric vehicle integrated thermal management system experiments. Applied Thermal Engineering. 269. 126002–126002. 4 indexed citations

Wu, Jun, et al.. (2024). Attentive multi-granularity perception network for person search. Information Sciences. 681. 121191–121191. 12 indexed citations

Wu, Jun, et al.. (2024). RuMono: Fuzz Driver Synthesis for Rust Generic APIs. ACM Transactions on Software Engineering and Methodology. 34(6). 1–28.

Holden, Craig W., et al.. (2023). In the Blink of an Eye: Exchange-to-SIP Latency and Trade Classification Accuracy. SSRN Electronic Journal. 1 indexed citations

Wei, Kang, Jun Li, Chuan Ma, et al.. (2023). Personalized Federated Learning With Differential Privacy and Convergence Guarantee. IEEE Transactions on Information Forensics and Security. 18. 4488–4503. 97 indexed citations breakdown →

Hu, Die, et al.. (2022). Deep-Learning-Based Initial Access Method for Millimeter-Wave MIMO Systems. IEEE Wireless Communications Letters. 11(5). 1067–1071. 5 indexed citations

Zhao, Cairong, et al.. (2020). Deep Fusion Feature Representation Learning With Hard Mining Center-Triplet Loss for Person Re-Identification. IEEE Transactions on Multimedia. 22(12). 3180–3195. 82 indexed citations

Hu, Die, Yonghao Zhang, Lianghua He, & Jun Wu. (2019). Low-Complexity Deep-Learning-Based DOA Estimation for Hybrid Massive MIMO Systems With Uniform Circular Arrays. IEEE Wireless Communications Letters. 9(1). 83–86. 79 indexed citations

10.

Xiong, Mingliang, Mingqing Liu, Qingqing Zhang, et al.. (2018). TDMA in Adaptive Resonant Beam Charging for IoT Devices. IEEE Internet of Things Journal. 6(1). 867–877. 21 indexed citations

11.

Hu, Die, Wei Zhang, Lianghua He, & Jun Wu. (2018). Secure Transmission in Multi-Cell Multi-User Massive MIMO Systems With an Active Eavesdropper. IEEE Wireless Communications Letters. 8(1). 85–88. 14 indexed citations

12.

Wen, Fang, Qingqing Zhang, Qingwen Liu, Jun Wu, & Pengfei Xia. (2018). Fair Scheduling in Resonant Beam Charging for IoT Devices. IEEE Internet of Things Journal. 6(1). 641–653. 31 indexed citations

13.

Zhang, Qingqing, et al.. (2018). Optimal Resonant Beam Charging for Electronic Vehicles in Internet of Intelligent Vehicles. IEEE Internet of Things Journal. 6(1). 6–14. 17 indexed citations

14.

Cheng, Songlin, Rui Wang, Jun Wu, Wei Zhang, & Zhijun Fang. (2018). Performance Analysis and Beamforming Designs of MIMO AF Relaying With Hardware Impairments. IEEE Transactions on Vehicular Technology. 67(7). 6229–6243. 11 indexed citations

15.

Huang, Xin‐Lin, et al.. (2016). Performance Analysis of KMV-Cast with Imperfect Prior Knowledge. 1–5. 1 indexed citations

16.

Wu, Jun. (2012). Design of Measuring Device for Deformation of Airplane's Wing Structure. Yibiao jishu yu chuanganqi. 1 indexed citations

17.

Wu, Jun, et al.. (2010). Sensor Optimal Placement Algorithm Based on Coverage Rate. Jisuanji gongcheng. 36(3). 94–96. 2 indexed citations

18.

Wu, Jun. (2008). Design method of straight-conjugate internal gear pump. 2 indexed citations

19.

Wu, Jun. (2006). Study on the optimizing method and technique of fire station planning. Fire Science and Technology. 1 indexed citations

20.

Wu, Jun. (2005). Design of Remote Communication in Substation Automation Based on Trusted Computing Method. Dianli xitong zidonghua.

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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