Zhenkun Wang

2.9k total citations
118 papers, 2.1k citations indexed

About

Zhenkun Wang is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Electrical and Electronic Engineering. According to data from OpenAlex, Zhenkun Wang has authored 118 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 38 papers in Computational Theory and Mathematics and 20 papers in Electrical and Electronic Engineering. Recurrent topics in Zhenkun Wang's work include Advanced Multi-Objective Optimization Algorithms (38 papers), Metaheuristic Optimization Algorithms Research (31 papers) and Magnetic properties of thin films (15 papers). Zhenkun Wang is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (38 papers), Metaheuristic Optimization Algorithms Research (31 papers) and Magnetic properties of thin films (15 papers). Zhenkun Wang collaborates with scholars based in China, Hong Kong and Singapore. Zhenkun Wang's co-authors include Qingfu Zhang, Genghui Li, Maoguo Gong, Yew-Soon Ong, Licheng Jiao, Aimin Zhou, Hisao Ishibuchi, Jianping Luo, Qingfang Liu and Jianbo Wang and has published in prestigious journals such as Journal of Applied Physics, Macromolecules and Scientific Reports.

In The Last Decade

Zhenkun Wang

107 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhenkun Wang China 28 950 886 257 245 205 118 2.1k
Tianjun Liao China 27 676 0.7× 455 0.5× 30 0.1× 663 2.7× 144 0.7× 102 2.4k
Allan N. Zhang Singapore 21 394 0.4× 216 0.2× 118 0.5× 196 0.8× 360 1.8× 79 1.6k
Yuyan Han China 34 808 0.9× 425 0.5× 105 0.4× 252 1.0× 57 0.3× 136 3.9k
M. Premkumar India 37 1.9k 2.0× 669 0.8× 107 0.4× 1.6k 6.7× 47 0.2× 137 4.2k
Pan Wang China 24 647 0.7× 82 0.1× 305 1.2× 558 2.3× 96 0.5× 184 2.5k
Lihong Guo China 27 1.2k 1.2× 524 0.6× 48 0.2× 376 1.5× 20 0.1× 83 2.7k
Shi Cheng China 32 2.0k 2.1× 945 1.1× 52 0.2× 1.4k 5.8× 35 0.2× 172 4.8k
Luca P. Carloni United States 35 474 0.5× 357 0.4× 137 0.5× 3.2k 13.2× 279 1.4× 206 5.2k
Yichen Zhang China 37 3.4k 3.6× 551 0.6× 244 0.9× 990 4.0× 137 0.7× 194 5.2k
Conor Ryan Ireland 21 1.6k 1.7× 275 0.3× 13 0.1× 361 1.5× 154 0.8× 190 2.7k

Countries citing papers authored by Zhenkun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Zhenkun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhenkun Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Zhenkun Wang. A scholar is included among the top collaborators of Zhenkun 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 Zhenkun Wang. Zhenkun 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.
2.
Wang, Zhenkun, et al.. (2024). Multiobjective Optimization Problem With Hardly Dominated Boundaries: Benchmark, Analysis, and Indicator-Based Algorithm. IEEE Transactions on Evolutionary Computation. 29(4). 1070–1084. 5 indexed citations
3.
Sun, Rui, et al.. (2024). Learning Encodings for Constructive Neural Combinatorial Optimization Needs to Regret. Proceedings of the AAAI Conference on Artificial Intelligence. 38(18). 20803–20811. 2 indexed citations
4.
Chen, Jing, et al.. (2024). Towards Lightweight Underwater Depth Estimation. 1442–1445. 1 indexed citations
5.
Song, Shenmin, et al.. (2024). A Flexible Ranking-Based Competitive Swarm Optimizer for Large-Scale Continuous Multiobjective Optimization. IEEE Transactions on Evolutionary Computation. 29(1). 247–261. 8 indexed citations
6.
Liu, Yilu, Qingfu Zhang, & Zhenkun Wang. (2024). Community Opinion Maximization in Social Networks. IEEE Transactions on Evolutionary Computation. 29(5). 1760–1773. 4 indexed citations
7.
Li, Genghui, et al.. (2024). Decomposition with adaptive composite norm for evolutionary multi-objective combinatorial optimization. Swarm and Evolutionary Computation. 86. 101503–101503. 5 indexed citations
8.
Li, Genghui, Zhenkun Wang, Weifeng Gao, Laizhong Cui, & Qingfu Zhang. (2024). Adaptive Multi/Many-Objective Transformation for Constrained Optimization. IEEE Transactions on Systems Man and Cybernetics Systems. 55(1). 721–734. 4 indexed citations
9.
Wang, Huajun, Genghui Li, & Zhenkun Wang. (2023). Fast SVM classifier for large-scale classification problems. Information Sciences. 642. 119136–119136. 60 indexed citations
10.
Wang, Zhenkun, et al.. (2023). Decomposition-Based Multi-Objective Evolutionary Algorithm with Model-Based Ideal Point Estimation. Proceedings of the Genetic and Evolutionary Computation Conference. 21. 768–776. 1 indexed citations
11.
Wang, Zhenkun, et al.. (2023). Toward Evolutionary Multitask Convolutional Neural Architecture Search. IEEE Transactions on Evolutionary Computation. 28(3). 682–695. 13 indexed citations
12.
Li, Genghui, et al.. (2023). Surrogate-Assisted Evolutionary Algorithm With Model and Infill Criterion Auto-Configuration. IEEE Transactions on Evolutionary Computation. 28(4). 1114–1126. 27 indexed citations
13.
Li, Genghui, et al.. (2023). Differential evolution with an adaptive penalty coefficient mechanism and a search history exploitation mechanism. Expert Systems with Applications. 230. 120530–120530. 8 indexed citations
14.
Wang, Zhenkun, et al.. (2021). Choose Appropriate Subproblems for Collaborative Modeling in Expensive Multiobjective Optimization. IEEE Transactions on Cybernetics. 53(1). 483–496. 54 indexed citations
15.
Wang, Zhenkun, Hui‐Ling Zhen, Jingda Deng, et al.. (2021). Multiobjective Optimization-Aided Decision-Making System for Large-Scale Manufacturing Planning. IEEE Transactions on Cybernetics. 52(8). 8326–8339. 48 indexed citations
16.
Luo, Jianping, Abhishek Gupta, Yew-Soon Ong, & Zhenkun Wang. (2018). Evolutionary Optimization of Expensive Multiobjective Problems With Co-Sub-Pareto Front Gaussian Process Surrogates. IEEE Transactions on Cybernetics. 49(5). 1708–1721. 72 indexed citations
17.
Wang, Zhenkun, Yew-Soon Ong, Jianyong Sun, Abhishek Gupta, & Qingfu Zhang. (2018). A Generator for Multiobjective Test Problems With Difficult-to-Approximate Pareto Front Boundaries. IEEE Transactions on Evolutionary Computation. 23(4). 556–571. 67 indexed citations
18.
Wang, Zhenkun, Yew-Soon Ong, & Hisao Ishibuchi. (2018). On Scalable Multiobjective Test Problems With Hardly Dominated Boundaries. IEEE Transactions on Evolutionary Computation. 23(2). 217–231. 83 indexed citations
19.
Li, Hao, Yew-Soon Ong, Maoguo Gong, & Zhenkun Wang. (2018). Evolutionary Multitasking Sparse Reconstruction: Framework and Case Study. IEEE Transactions on Evolutionary Computation. 23(5). 733–747. 76 indexed citations
20.
Wang, Zhenkun, Qingfu Zhang, & Hui Li. (2015). Balancing Convergence and Diversity by Using Two Different Reproduction Operators in MOEA/D: Some Preliminary Work. 2849–2854. 11 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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