Shir Li Wang

474 total citations
32 papers, 263 citations indexed

About

Shir Li Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Shir Li Wang has authored 32 papers receiving a total of 263 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 5 papers in Computational Theory and Mathematics. Recurrent topics in Shir Li Wang's work include Metaheuristic Optimization Algorithms Research (6 papers), Evolutionary Algorithms and Applications (6 papers) and Advanced Multi-Objective Optimization Algorithms (5 papers). Shir Li Wang is often cited by papers focused on Metaheuristic Optimization Algorithms Research (6 papers), Evolutionary Algorithms and Applications (6 papers) and Advanced Multi-Objective Optimization Algorithms (5 papers). Shir Li Wang collaborates with scholars based in Malaysia, China and Australia. Shir Li Wang's co-authors include Theam Foo Ng, Bahbibi Rahmatullah, Haidi Ibrahim, Rostam Affendi Hamzah, Can Yang, Siew Chin Neoh, Zhaoyan Liu, Bin Zhang, Rafidah Zainon and Embong Zunaina and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Chemosphere.

In The Last Decade

Shir Li Wang

28 papers receiving 258 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shir Li Wang Malaysia 10 85 74 38 32 30 32 263
Balajee Maram India 9 108 1.3× 109 1.5× 78 2.1× 7 0.2× 19 0.6× 65 334
Henry Gouk United Kingdom 6 92 1.1× 163 2.2× 31 0.8× 12 0.4× 20 0.7× 14 300
Linus Ericsson United Kingdom 2 59 0.7× 102 1.4× 21 0.6× 12 0.4× 19 0.6× 3 221
Mostafa E. A. Ibrahim Egypt 10 118 1.4× 62 0.8× 79 2.1× 16 0.5× 14 0.5× 29 343
Sapiah Sakri Saudi Arabia 7 59 0.7× 205 2.8× 50 1.3× 8 0.3× 23 0.8× 16 374
Diego Peteiro-Barral Spain 8 46 0.5× 150 2.0× 26 0.7× 6 0.2× 25 0.8× 15 296
Saravanan Alagarsamy India 11 121 1.4× 82 1.1× 86 2.3× 8 0.3× 38 1.3× 36 294
Emanuel Ben-Baruch Cayman Islands 3 199 2.3× 249 3.4× 41 1.1× 21 0.7× 20 0.7× 3 400
Asaf Noy Cayman Islands 4 205 2.4× 256 3.5× 42 1.1× 21 0.7× 20 0.7× 6 409
Itamar Friedman Cayman Islands 5 195 2.3× 251 3.4× 41 1.1× 21 0.7× 19 0.6× 6 391

Countries citing papers authored by Shir Li Wang

Since Specialization
Citations

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

Fields of papers citing papers by Shir Li Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shir Li Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Shir Li Wang. A scholar is included among the top collaborators of Shir Li 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 Shir Li Wang. Shir Li 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.
Rahman, Norazah Abd, et al.. (2025). ENSEMBLE LEARNING IN EDUCATIONAL DATA ANALYSIS FOR IMPROVED PREDICTION OF STUDENT PERFORMANCE: A LITERATURE REVIEW. Zenodo (CERN European Organization for Nuclear Research). 7(24). 887–902.
4.
Rahman, Norazah Abd, Shir Li Wang, Theam Foo Ng, & Amr S. Ghoneim. (2024). Artificial Intelligence in Education: A Systematic Review of Machine Learning for Predicting Student Performance. Journal of Advanced Research in Applied Sciences and Engineering Technology. 54(1). 198–221.
5.
Wang, Shir Li, et al.. (2023). Convolutional neural network optimized by differential evolution for electrocardiogram classification. Multimedia Tools and Applications. 82(29). 45811–45837. 4 indexed citations
6.
Zhang, Bin, Bahbibi Rahmatullah, Shir Li Wang, et al.. (2023). A variable dimensional chaotic map-based medical image encryption algorithm with multi-mode. Medical & Biological Engineering & Computing. 61(11). 2971–3002. 6 indexed citations
7.
Rahmatullah, Bahbibi, et al.. (2022). CLASSIFICATION MODEL FOR BREAST CANCER MAMMOGRAMS. IIUM Engineering Journal. 23(1). 187–199. 13 indexed citations
8.
Yuan, Lei, et al.. (2022). A Federated Learning Framework Based on Incremental Weighting and Diversity Selection for Internet of Vehicles. Electronics. 11(22). 3668–3668. 11 indexed citations
9.
Zhang, Bin, Bahbibi Rahmatullah, Shir Li Wang, & Zhaoyan Liu. (2022). A plain-image correlative semi-selective medical image encryption algorithm using enhanced 2D-logistic map. Multimedia Tools and Applications. 82(10). 15735–15762. 18 indexed citations
10.
Yuan, Lei, et al.. (2022). OES-Fed: a federated learning framework in vehicular network based on noise data filtering. PeerJ Computer Science. 8. e1101–e1101. 9 indexed citations
11.
Wang, Shir Li, et al.. (2022). Review of ECG detection and classification based on deep learning: Coherent taxonomy, motivation, open challenges and recommendations. Biomedical Signal Processing and Control. 74. 103493–103493. 42 indexed citations
12.
Wang, Shir Li, et al.. (2021). A CNN based Handwritten Numeral Recognition Model for Four Arithmetic Operations. Procedia Computer Science. 192. 4416–4424. 9 indexed citations
13.
Wang, Shir Li, et al.. (2021). Smart Differentiation System using Self-Adaptive Ensemble-based Differential Evolution (SAEDE) as a Learning Aid for Learning Differentiation. SHILAP Revista de lepidopterología. 8(3). 50–59. 1 indexed citations
14.
Hamzah, Rostam Affendi, et al.. (2021). Quality Assessment Methods to Evaluate the Performance of Edge Detection Algorithms for Digital Image: A Systematic Literature Review. IEEE Access. 9. 87763–87776. 27 indexed citations
15.
Wang, Shir Li, et al.. (2019). Insights into the effects of control parameters and mutation strategy on self-adaptive ensemble-based differential evolution. Information Sciences. 514. 203–233. 21 indexed citations
16.
Wang, Shir Li, et al.. (2018). Self-adaptive Ensemble Based Differential Evolution. International Journal of Machine Learning and Computing. 8(3). 286–293. 6 indexed citations
17.
Wang, Shir Li, et al.. (2018). An Overview on the Application of Self-Adaptive Differential Evolution. 82–86. 1 indexed citations
18.
Wang, Shir Li, et al.. (2015). Self-adapting approach in parameter tuning for differential evolution. 113–119. 3 indexed citations
19.
Wang, Shir Li, Kamran Shafi, Chris Lokan, & Hussein A. Abbass. (2010). Adversarial learning: the impact of statistical sample selection techniques on neural ensembles. Evolving Systems. 1(3). 181–197. 2 indexed citations
20.
Lim, Chee Peng, et al.. (2009). Use of the circle segments visualization technique for neural network feature selection and analysis. Neurocomputing. 73(4-6). 613–621. 3 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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