Lingjun Zhao

1.2k total citations
53 papers, 816 citations indexed

About

Lingjun Zhao is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Lingjun Zhao has authored 53 papers receiving a total of 816 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Electrical and Electronic Engineering, 15 papers in Artificial Intelligence and 13 papers in Computer Vision and Pattern Recognition. Recurrent topics in Lingjun Zhao's work include Indoor and Outdoor Localization Technologies (17 papers), Underwater Vehicles and Communication Systems (10 papers) and Sparse and Compressive Sensing Techniques (7 papers). Lingjun Zhao is often cited by papers focused on Indoor and Outdoor Localization Technologies (17 papers), Underwater Vehicles and Communication Systems (10 papers) and Sparse and Compressive Sensing Techniques (7 papers). Lingjun Zhao collaborates with scholars based in China, Japan and Hong Kong. Lingjun Zhao's co-authors include Huakun Huang, Shuxue Ding, Gangyao Kuang, Jun Lü, Na Wang, Ganggang Dong, Huawei Huang, Li Li, Xiaoqing Zhou and Xiang Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Communications Magazine.

In The Last Decade

Lingjun Zhao

48 papers receiving 793 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lingjun Zhao China 15 204 185 134 134 126 53 816
Chaocan Xiang China 18 572 2.8× 167 0.9× 149 1.1× 178 1.3× 307 2.4× 72 1.1k
Fakhrul Alam New Zealand 19 688 3.4× 147 0.8× 191 1.4× 125 0.9× 313 2.5× 84 1.3k
Jörg Blankenbach Germany 15 411 2.0× 269 1.5× 175 1.3× 76 0.6× 59 0.5× 76 723
Nobuo Kawaguchi Japan 17 327 1.6× 133 0.7× 89 0.7× 263 2.0× 188 1.5× 143 1.1k
Michael Peter Germany 16 110 0.5× 243 1.3× 77 0.6× 198 1.5× 100 0.8× 53 802
Chen Song China 12 576 2.8× 64 0.3× 60 0.4× 95 0.7× 175 1.4× 60 1.0k
Hamada Rizk Japan 18 691 3.4× 182 1.0× 300 2.2× 124 0.9× 169 1.3× 70 1000
Qing Zhu China 14 36 0.2× 74 0.4× 65 0.5× 100 0.7× 115 0.9× 102 905
Vincent Havyarimana China 18 243 1.2× 154 0.8× 79 0.6× 200 1.5× 150 1.2× 37 920
Deepak Adhikari China 14 83 0.4× 85 0.5× 55 0.4× 134 1.0× 86 0.7× 33 564

Countries citing papers authored by Lingjun Zhao

Since Specialization
Citations

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

Fields of papers citing papers by Lingjun Zhao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lingjun Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Lingjun Zhao. A scholar is included among the top collaborators of Lingjun Zhao 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 Lingjun Zhao. Lingjun Zhao 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.
Huang, Huakun, et al.. (2025). Time Series Focused Neural Network for Accurate Wireless Human Gesture Recognition. IEEE Transactions on Network Science and Engineering. 13. 118–129.
2.
Wang, Chenyang, et al.. (2025). Wi-Fi Sensing Based on Deep Supervised Dictionary Learning for Robust Device-Free Localization. IEEE Transactions on Vehicular Technology. 74(8). 12842–12852.
3.
Huang, Huakun, et al.. (2025). WiPE: Privacy-Friendly WiFi-Based Human Pose Estimation on Consumer Platform. IEEE Transactions on Consumer Electronics. 71(2). 5127–5135.
4.
Liu, Peng, et al.. (2025). Time Series Remote Sensing Image Classification with a Data-Driven Active Deep Learning Approach. Sensors. 25(6). 1718–1718. 1 indexed citations
5.
Huang, Huakun, et al.. (2025). Non-invasive human thermal adaptive behavior recognition based on privacy-friendly WiFi sensing in buildings: A review. Building Simulation. 18(5). 979–998. 1 indexed citations
6.
Huang, Huakun, et al.. (2024). An Effective Scheme to Solve Critical Data Missing Problems for IoT-Based Smart Energy Management. IEEE Internet of Things Journal. 12(4). 4466–4474. 2 indexed citations
7.
Huang, Huakun, et al.. (2024). TSHNN: Temporal-Spatial Hybrid Neural Network for Cognitive Wireless Human Activity Recognition. IEEE Transactions on Cognitive Communications and Networking. 10(6). 2088–2101. 10 indexed citations
8.
Zhao, Lingjun, et al.. (2023). Intelligent wireless sensing driven metaverse: A survey. Computer Communications. 214. 46–56. 24 indexed citations
9.
Huang, Haiping, et al.. (2023). An IoT and machine learning enhanced framework for real-time digital human modeling and motion simulation. Computer Communications. 212. 78–89. 2 indexed citations
10.
Huang, Huakun, et al.. (2023). Privacy-Preserving Smart Energy Management by Consumer-Electronic Chips and Federated Learning. IEEE Transactions on Consumer Electronics. 70(1). 2200–2209. 13 indexed citations
11.
Huang, Huakun, et al.. (2023). Federated Learning and Convex Hull Enhancement for Privacy Preserving WiFi-Based Device-Free Localization. IEEE Transactions on Consumer Electronics. 70(1). 2577–2585. 13 indexed citations
12.
Zhao, Lingjun, Huakun Huang, Weizheng Wang, & Zibin Zheng. (2023). An accurate approach of device-free localization with attention empowered residual network. Applied Soft Computing. 137. 110164–110164. 19 indexed citations
13.
Chen, Lajiao, et al.. (2023). A new multi-source remote sensing image sample dataset with high resolution for flood area extraction: GF-FloodNet. International Journal of Digital Earth. 16(1). 2522–2554. 22 indexed citations
14.
Huang, Huakun, et al.. (2023). SREM: Smart renewable energy management scheme with distributed learning and EV network. Engineering Reports. 6(5). 4 indexed citations
15.
16.
Min, Bonan, Yee Seng Chan, & Lingjun Zhao. (2020). Towards Few-Shot Event Mention Retrieval: An Evaluation Framework and A Siamese Network Approach. Language Resources and Evaluation. 1747–1752. 2 indexed citations
17.
Ding, Shuxue, et al.. (2019). $\ell_P$ Norm Independently Interpretable Regularization Based Sparse Coding for Highly Correlated Data. IEEE Access. 7. 53542–53554. 2 indexed citations
18.
Zhao, Lingjun, et al.. (2019). An Accurate and Robust Approach of Device-Free Localization With Convolutional Autoencoder. IEEE Internet of Things Journal. 6(3). 5825–5840. 64 indexed citations
19.
Zhao, Lingjun, et al.. (2018). Laparoscopic Management of Didelphys Uterus with a Chronically Inversed Right Uteri. Journal of Minimally Invasive Gynecology. 26(3). 386–387.
20.
Zhao, Lingjun, et al.. (2015). Geographical information system parallelization for spatial big data processing: a review. Cluster Computing. 19(1). 139–152. 53 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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