Xingjuan Cai

6.2k total citations · 4 hit papers
130 papers, 4.8k citations indexed

About

Xingjuan Cai is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Xingjuan Cai has authored 130 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Artificial Intelligence, 42 papers in Computational Theory and Mathematics and 32 papers in Computer Networks and Communications. Recurrent topics in Xingjuan Cai's work include Metaheuristic Optimization Algorithms Research (51 papers), Advanced Multi-Objective Optimization Algorithms (41 papers) and Evolutionary Algorithms and Applications (24 papers). Xingjuan Cai is often cited by papers focused on Metaheuristic Optimization Algorithms Research (51 papers), Advanced Multi-Objective Optimization Algorithms (41 papers) and Evolutionary Algorithms and Applications (24 papers). Xingjuan Cai collaborates with scholars based in China, Australia and Finland. Xingjuan Cai's co-authors include Zhihua Cui, Jinjun Chen, Yang Cao, Wensheng Zhang, Fei Xue, Jiangjiang Zhang, Wensheng Zhang, Gai‐Ge Wang, Shaojin Geng and Penghong Wang and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Xingjuan Cai

121 papers receiving 4.6k citations

Hit Papers

Detection of Malicious Code Variants Based on Deep Learning 2018 2026 2020 2023 2018 2020 2020 2019 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xingjuan Cai China 32 2.0k 1.4k 1.3k 749 682 130 4.8k
Nebojša Bačanin Serbia 42 2.6k 1.3× 1.2k 0.8× 899 0.7× 361 0.5× 898 1.3× 282 5.7k
Francesco Marcelloni Italy 37 2.4k 1.2× 727 0.5× 847 0.7× 363 0.5× 516 0.8× 212 4.9k
Laizhong Cui China 33 1.6k 0.8× 1.3k 0.9× 785 0.6× 550 0.7× 537 0.8× 148 3.5k
Shi‐Jinn Horng Taiwan 40 1.9k 1.0× 1.1k 0.8× 1.1k 0.8× 635 0.8× 1.9k 2.8× 214 6.0k
Zhongzhi Shi China 36 2.6k 1.3× 632 0.4× 1.3k 1.0× 973 1.3× 1.1k 1.6× 383 5.1k
Zhihua Cui China 41 3.8k 1.9× 1.8k 1.3× 1.2k 1.0× 1.4k 1.9× 1.1k 1.6× 249 8.0k
Joshua Zhexue Huang China 38 2.9k 1.4× 1.2k 0.8× 1.3k 1.0× 339 0.5× 1.3k 2.0× 195 5.5k
Sanjit A. Seshia United States 42 2.9k 1.4× 1.4k 1.0× 1.1k 0.8× 2.1k 2.7× 740 1.1× 197 7.3k
Alireza Jolfaei Australia 43 2.1k 1.1× 2.2k 1.6× 1.5k 1.1× 195 0.3× 1.1k 1.7× 212 6.3k
Farhad Soleimanian Gharehchopogh Iran 48 4.2k 2.1× 1.3k 0.9× 982 0.8× 1.6k 2.2× 874 1.3× 156 7.7k

Countries citing papers authored by Xingjuan Cai

Since Specialization
Citations

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

Fields of papers citing papers by Xingjuan Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xingjuan Cai

This figure shows the co-authorship network connecting the top 25 collaborators of Xingjuan Cai. A scholar is included among the top collaborators of Xingjuan Cai 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 Xingjuan Cai. Xingjuan Cai 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
2.
Qin, Juan‐Juan, Pei Dong, Qian Guo, et al.. (2024). Intersection-union dual-stream cross-attention Lova-SwinUnet for skin cancer hair segmentation and image repair. Computers in Biology and Medicine. 180. 108931–108931. 2 indexed citations
3.
Cai, Xingjuan, et al.. (2024). Dynamic deadline constrained multi-objective workflow scheduling in multi-cloud environments. Expert Systems with Applications. 258. 125168–125168. 6 indexed citations
4.
Zhang, Jingbo, et al.. (2024). Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables. Computer Modeling in Engineering & Sciences. 140(1). 363–383. 1 indexed citations
5.
Li, Binbin, et al.. (2024). A Multi‐Workflow Scheduling Approach With Explicit Evolutionary Multi‐Objective Multi‐Task Optimization Algorithm in Cloud Environment. Concurrency and Computation Practice and Experience. 37(1). 1 indexed citations
6.
Cui, Zhihua, et al.. (2024). An adaptive differential evolution algorithm based on archive reuse. Information Sciences. 668. 120524–120524. 9 indexed citations
7.
Cai, Xingjuan, et al.. (2024). Explicable recommendation model based on a time‐assisted knowledge graph and many‐objective optimization algorithm. Concurrency and Computation Practice and Experience. 36(21).
8.
Cui, Zhihua, et al.. (2023). A many-objective evolutionary algorithm based on constraints for collaborative computation offloading. Swarm and Evolutionary Computation. 77. 101244–101244. 21 indexed citations
9.
Zhang, Yan, et al.. (2023). Dynamic multi-objective workflow scheduling for combined resources in cloud. Simulation Modelling Practice and Theory. 129. 102835–102835. 4 indexed citations
10.
Cai, Xingjuan, et al.. (2023). Dynamic multi-objective evolutionary algorithm based on knowledge transfer. Information Sciences. 636. 118886–118886. 26 indexed citations
11.
Zhang, Weiquan, et al.. (2023). Cross‐modal person re‐identification based on deep attention hash learning. Concurrency and Computation Practice and Experience. 35(28).
12.
Zhang, Jiangjiang, et al.. (2021). A coordinated many-objective evolutionary algorithm using random adaptive parameters. Applied Intelligence. 52(7). 7248–7270. 1 indexed citations
13.
Cai, Xingjuan, Y. Lan, Zhixia Zhang, et al.. (2021). A Many-Objective Optimization Based Federal Deep Generation Model for Enhancing Data Processing Capability in IoT. IEEE Transactions on Industrial Informatics. 19(1). 561–569. 40 indexed citations
14.
Cai, Xingjuan, Zhaoming Hu, & Jinjun Chen. (2020). A many-objective optimization recommendation algorithm based on knowledge mining. Information Sciences. 537. 148–161. 91 indexed citations
15.
Sun, Youqiang, et al.. (2020). Biobjective Emergency Logistics Scheduling Model Based on Uncertain Traffic Conditions. Mathematical Problems in Engineering. 2020. 1–15. 10 indexed citations
16.
Xu, Jialei, Zhixia Zhang, Zhaoming Hu, Lei Du, & Xingjuan Cai. (2020). A many-objective optimized task allocation scheduling model in cloud computing. Applied Intelligence. 51(6). 3293–3310. 32 indexed citations
17.
Cai, Xingjuan, Jiangjiang Zhang, Hao Liang, Lei Wang, & Qidi Wu. (2019). An ensemble bat algorithm for large-scale optimization. International Journal of Machine Learning and Cybernetics. 10(11). 3099–3113. 30 indexed citations
18.
Wang, Penghong, Jiangjiang Zhang, Zhihua Cui, et al.. (2019). A Novel Bat Algorithm with Multiple Strategies Coupling for Numerical Optimization. Mathematics. 7(2). 135–135. 111 indexed citations
19.
Cui, Zhihua, Xingjuan Cai, & Zhongzhi Shi. (2011). Social emotional optimization algorithm with group decision. Scientific Research and Essays. 6(22). 4848–4855. 3 indexed citations
20.
Cui, Zhihua, et al.. (2010). A hybrid group search optimizer with metropolis rule. International Conference on Modelling, Identification and Control. 556–561. 5 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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