Jing Yang

5.8k total citations · 2 hit papers
143 papers, 3.8k citations indexed

About

Jing Yang is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Jing Yang has authored 143 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Electrical and Electronic Engineering, 62 papers in Computer Networks and Communications and 24 papers in Artificial Intelligence. Recurrent topics in Jing Yang's work include Energy Harvesting in Wireless Networks (39 papers), Advanced MIMO Systems Optimization (38 papers) and Age of Information Optimization (25 papers). Jing Yang is often cited by papers focused on Energy Harvesting in Wireless Networks (39 papers), Advanced MIMO Systems Optimization (38 papers) and Age of Information Optimization (25 papers). Jing Yang collaborates with scholars based in United States, China and Canada. Jing Yang's co-authors include Şennur Ulukuş, Omur Ozel, Aylin Yener, Kaya Tutuncuoglu, Jingxian Wu, Songtao Feng, Xianwen Wu, Berk Gurakan, Xiaorong Hou and Cong Shen and has published in prestigious journals such as Nature Communications, Applied Physics Letters and IEEE Transactions on Information Theory.

In The Last Decade

Jing Yang

131 papers receiving 3.8k citations

Hit Papers

Transmission with Energy Harvesting Nodes in Fading Wirel... 2011 2026 2016 2021 2011 2011 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jing Yang United States 24 3.1k 1.5k 316 223 172 143 3.8k
Elif Uysal‐Biyikoglu Türkiye 25 2.5k 0.8× 3.2k 2.1× 1.1k 3.5× 106 0.5× 130 0.8× 101 3.9k
Ke Xiong China 31 2.9k 0.9× 1.6k 1.0× 81 0.3× 1.1k 4.9× 89 0.5× 235 3.8k
Ioannis Krikidis Cyprus 39 7.6k 2.5× 4.2k 2.8× 46 0.1× 1.0k 4.6× 119 0.7× 276 8.0k
Shugong Xu China 31 4.1k 1.3× 3.0k 2.0× 16 0.1× 454 2.0× 100 0.6× 212 5.2k
Bo Tan Finland 22 891 0.3× 660 0.4× 10 0.0× 321 1.4× 339 2.0× 118 1.6k
Muhammad Rehan Pakistan 33 792 0.3× 1.3k 0.9× 12 0.0× 97 0.4× 105 0.6× 215 3.2k
G. Betta Italy 30 1.0k 0.3× 332 0.2× 13 0.0× 56 0.3× 256 1.5× 147 2.5k
Kaiming Shen China 21 2.2k 0.7× 909 0.6× 7 0.0× 968 4.3× 116 0.7× 86 3.0k
L. Giarré Italy 20 226 0.1× 516 0.3× 18 0.1× 132 0.6× 85 0.5× 113 1.9k
Arokiaswami Alphones Singapore 35 3.1k 1.0× 364 0.2× 7 0.0× 1.7k 7.7× 288 1.7× 207 3.7k

Countries citing papers authored by Jing Yang

Since Specialization
Citations

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

Fields of papers citing papers by Jing Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jing Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Jing Yang. A scholar is included among the top collaborators of Jing Yang 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 Jing Yang. Jing Yang 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.
Yang, Jing, et al.. (2025). Meta-knowledge random attention update network for few-shot and anti-noise remaining useful life prediction. Advanced Engineering Informatics. 65. 103358–103358.
2.
Yang, Jing, et al.. (2025). Prior task aware-augmented meta learning for early state-of-health estimation of lithium-ion batteries. Energy. 322. 135648–135648. 2 indexed citations
3.
Yang, Kun, et al.. (2024). Offline Reinforcement Learning for Wireless Network Optimization With Mixture Datasets. IEEE Transactions on Wireless Communications. 23(10). 12703–12716. 9 indexed citations
4.
Yin, Ming, et al.. (2024). Toward General Function Approximation in Nonstationary Reinforcement Learning. IEEE Journal on Selected Areas in Information Theory. 5. 190–206. 1 indexed citations
5.
Shen, Cong, et al.. (2023). Random Orthogonalization for Federated Learning in Massive MIMO Systems. IEEE Transactions on Wireless Communications. 23(3). 2469–2485. 9 indexed citations
6.
Luo, Yu, et al.. (2022). Reinforcement Learning Enabled Intelligent Energy Attack in Green IoT Networks. IEEE Transactions on Information Forensics and Security. 17. 644–658. 11 indexed citations
7.
Feng, Songtao & Jing Yang. (2022). Precoding and Scheduling for AoI Minimization in MIMO Broadcast Channels. IEEE Transactions on Information Theory. 68(8). 5185–5202. 13 indexed citations
8.
Shen, Cong, Jing Yang, & Jie Xu. (2022). On Federated Learning with Energy Harvesting Clients. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 8657–8661. 11 indexed citations
9.
Arafa, Ahmed, Jing Yang, Şennur Ulukuş, & H. Vincent Poor. (2021). Timely Status Updating Over Erasure Channels Using an Energy Harvesting Sensor: Single and Multiple Sources. IEEE Transactions on Green Communications and Networking. 6(1). 6–19. 24 indexed citations
10.
Feng, Songtao & Jing Yang. (2021). Age of Information Minimization for an Energy Harvesting Source With Updating Erasures: Without and With Feedback. IEEE Transactions on Communications. 69(8). 5091–5105. 56 indexed citations
11.
Shen, Cong, et al.. (2021). Federated Multi-armed Bandits with Personalization.. International Conference on Artificial Intelligence and Statistics. 2917–2925. 2 indexed citations
12.
Yang, Jing, et al.. (2020). Cost-Aware Cascading Bandits. IEEE Transactions on Signal Processing. 68. 3692–3706. 7 indexed citations
13.
Xiong, Wei, et al.. (2020). Decentralized Multi-player Multi-armed Bandits with No Collision Information. International Conference on Artificial Intelligence and Statistics. 1519–1528. 2 indexed citations
14.
Yang, Jing, et al.. (2019). Dynamics of Double-Beam System with Various Symmetric Boundary Conditions Traversed by a Moving Force: Analytical Analyses. Applied Sciences. 9(6). 1218–1218. 5 indexed citations
15.
Yang, Jing, et al.. (2019). Non-Asymptotic Achievable Rates for Gaussian Energy-Harvesting Channels: Save-and-Transmit and Best-Effort. IEEE Transactions on Information Theory. 65(11). 7233–7252. 1 indexed citations
16.
Wu, Jingxian, et al.. (2019). Optimum Distributed Estimation of a Spatially Correlated Random Field. IEEE Transactions on Signal and Information Processing over Networks. 5(4). 739–752. 4 indexed citations
17.
Yang, Jing, et al.. (2018). Cost-Aware Learning and Optimization for Opportunistic Spectrum Access. IEEE Transactions on Cognitive Communications and Networking. 5(1). 15–27. 7 indexed citations
18.
Wu, Jingxian, et al.. (2017). Optimum PMU placement for power system state estimation. 1–5. 3 indexed citations
19.
Wu, Xianwen, Jing Yang, & Jingxian Wu. (2017). Optimal Status Update for Age of Information Minimization With an Energy Harvesting Source. IEEE Transactions on Green Communications and Networking. 2(1). 193–204. 203 indexed citations
20.
Yang, Jing. (2012). Research for wireless sensor networks quality of service on the ZigBee protocol. Electronic Design Engineering. 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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