Jun Wang

45.9k total citations · 16 hit papers
953 papers, 34.5k citations indexed

About

Jun Wang is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Networks and Communications. According to data from OpenAlex, Jun Wang has authored 953 papers receiving a total of 34.5k indexed citations (citations by other indexed papers that have themselves been cited), including 319 papers in Artificial Intelligence, 269 papers in Control and Systems Engineering and 228 papers in Computer Networks and Communications. Recurrent topics in Jun Wang's work include Neural Networks and Applications (209 papers), Neural Networks Stability and Synchronization (132 papers) and Advanced Memory and Neural Computing (79 papers). Jun Wang is often cited by papers focused on Neural Networks and Applications (209 papers), Neural Networks Stability and Synchronization (132 papers) and Advanced Memory and Neural Computing (79 papers). Jun Wang collaborates with scholars based in China, Hong Kong and United States. Jun Wang's co-authors include Zhouhua Peng, Qingshan Liu, Zhigang Zeng, Youshen Xia, Dan Wang, Zheng Yan, Jinde Cao, Qing‐Long Han, Zhenyuan Guo and Yunong Zhang and has published in prestigious journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and Applied Physics Letters.

In The Last Decade

Jun Wang

890 papers receiving 33.6k citations

Hit Papers

Introduction to artificial neural systems 1992 2026 2003 2014 1992 2002 2020 2005 2020 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jun Wang China 100 12.6k 11.2k 11.2k 7.3k 4.5k 953 34.5k
Brian D. O. Anderson Australia 90 12.2k 1.0× 18.8k 1.7× 5.5k 0.5× 7.4k 1.0× 4.4k 1.0× 1.0k 39.5k
Lihua Xie Singapore 99 17.6k 1.4× 20.8k 1.9× 5.9k 0.5× 8.2k 1.1× 1.1k 0.2× 1.1k 40.8k
C. L. Philip Chen China 112 11.5k 0.9× 22.6k 2.0× 12.5k 1.1× 5.1k 0.7× 1.6k 0.3× 1.1k 48.6k
Zidong Wang China 136 35.8k 2.8× 38.5k 3.4× 17.0k 1.5× 8.1k 1.1× 6.2k 1.4× 1.2k 67.3k
Huijun Gao China 121 17.8k 1.4× 30.5k 2.7× 5.2k 0.5× 3.4k 0.5× 2.9k 0.7× 621 43.6k
Tingwen Huang China 94 23.6k 1.9× 12.5k 1.1× 7.5k 0.7× 10.3k 1.4× 9.1k 2.0× 1.1k 38.0k
Xinghuo Yu Australia 97 13.9k 1.1× 26.5k 2.4× 3.2k 0.3× 11.8k 1.6× 4.7k 1.0× 892 41.9k
Qing‐Long Han Australia 125 31.4k 2.5× 34.4k 3.1× 6.2k 0.6× 7.4k 1.0× 2.8k 0.6× 723 50.3k
Dimitri P. Bertsekas United States 73 16.5k 1.3× 7.6k 0.7× 8.8k 0.8× 11.4k 1.6× 993 0.2× 262 45.9k
Hamid Reza Karimi China 94 10.3k 0.8× 21.0k 1.9× 3.2k 0.3× 3.4k 0.5× 1.8k 0.4× 956 30.6k

Countries citing papers authored by Jun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Jun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Wang. A scholar is included among the top collaborators of Jun Wang 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 Wang. Jun Wang 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.
Wang, Jun, et al.. (2025). Minority Support Defeats Majority Opposition? Equity Balance and Strategic Attention in Chinese SOEs. Academy of Management Proceedings. 2025(1).
2.
Wang, Jun, et al.. (2024). Enhanced cubic function negative-determination Lemma on stability analysis for delayed neural networks via new analytical techniques. Journal of the Franklin Institute. 361(3). 1155–1166. 3 indexed citations
3.
Jin, Long, et al.. (2024). Noise-resistant sharpness-aware minimization in deep learning. Neural Networks. 181. 106829–106829. 2 indexed citations
4.
Wang, Jun, et al.. (2024). Wavelet neural network algorithm for hybrid GA in infrared CO2 gas sensor. SHILAP Revista de lepidopterología. 6. 200145–200145. 1 indexed citations
5.
Yang, Na, Yu Jing, Qi Liu, et al.. (2024). Solar driven enhanced adsorption of radioactive Cs+ and Sr2+ from nuclear wastewater by chitosan-based aerogel embedded with prussian blue analog. Journal of Hazardous Materials. 485. 136955–136955. 14 indexed citations
6.
Xue, Ke, Shuling Zhang, Zhicheng Li, et al.. (2024). State-of-health estimation for lithium-ion batteries using relaxation voltage under dynamic conditions. Journal of Energy Storage. 100. 113506–113506. 6 indexed citations
7.
Wang, Jun, et al.. (2024). Binary matrix factorization via collaborative neurodynamic optimization. Neural Networks. 176. 106348–106348. 2 indexed citations
9.
He, Xuanli, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein, & Trevor Cohn. (2024). SEEP: Training Dynamics Grounds Latent Representation Search for Mitigating Backdoor Poisoning Attacks. Transactions of the Association for Computational Linguistics. 12. 996–1010. 1 indexed citations
10.
Wang, Jun, et al.. (2024). Multi-UAV adaptive super-twisting integral terminal sliding mode formation control. Engineering Research Express. 6(3). 35235–35235. 1 indexed citations
11.
Wang, Jun, et al.. (2023). A feature-recombinant asynchronous deep reservoir computing for modeling time series data. Applied Soft Computing. 151. 111167–111167. 2 indexed citations
12.
Wang, Jun, et al.. (2023). CAPKM++2.0: An upgraded version of the collaborative annealing power k-means++ clustering algorithm. Knowledge-Based Systems. 262. 110241–110241. 12 indexed citations
13.
Liu, Yang, et al.. (2023). Two-timescale recurrent neural networks for distributed minimax optimization. Neural Networks. 165. 527–539. 14 indexed citations
14.
Qiu, Shuang, Jun Fang, Nan Ma, et al.. (2023). Short-Term Prediction of PV Power Based on Combined Modal Decomposition and NARX-LSTM-LightGBM. Sustainability. 15(10). 8266–8266. 4 indexed citations
15.
Huang, Cong, Serdar Coskun, Jun Wang, Peng Mei, & Quan Shi. (2021). Robust $H_{\infty }$ Dynamic Output-Feedback Control for CACC With ROSSs Subject to RODAs. IEEE Transactions on Vehicular Technology. 71(1). 137–147. 21 indexed citations
16.
Peng, Zhouhua & Jun Wang. (2017). Output-Feedback Path-Following Control of Autonomous Underwater Vehicles Based on an Extended State Observer and Projection Neural Networks. IEEE Transactions on Systems Man and Cybernetics Systems. 48(4). 535–544. 303 indexed citations breakdown →
17.
Wang, Jun, et al.. (2015). Mathematics Interventions for Students with Learning Disabilities (LD) in Secondary School: A Review of the Literature.. 13(2). 207–235. 17 indexed citations
18.
Xia, Youshen & Jun Wang. (2015). Low-dimensional recurrent neural network-based Kalman filter for speech enhancement. Neural Networks. 67. 131–139. 44 indexed citations
19.
Wang, Jun, et al.. (2014). Josephsonπstate induced by valley polarization. Physical Review B. 89(6). 23 indexed citations
20.
Nokihara, Kiyoshi, et al.. (2002). Development of a simple and low cost manual synthesizer for chemical library construction. 2001. 61–64. 2 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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