Wanliang Wang

272 total papers · 3.3k total citations
166 papers, 2.3k citations indexed

About

Wanliang Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Wanliang Wang has authored 166 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Artificial Intelligence, 37 papers in Computer Vision and Pattern Recognition and 30 papers in Control and Systems Engineering. Recurrent topics in Wanliang Wang's work include Metaheuristic Optimization Algorithms Research (45 papers), Advanced Multi-Objective Optimization Algorithms (24 papers) and Scheduling and Optimization Algorithms (16 papers). Wanliang Wang is often cited by papers focused on Metaheuristic Optimization Algorithms Research (45 papers), Advanced Multi-Objective Optimization Algorithms (24 papers) and Scheduling and Optimization Algorithms (16 papers). Wanliang Wang collaborates with scholars based in China, United Kingdom and United States. Wanliang Wang's co-authors include Shengyong Chen, Xinli Xu, Li Li, Xin‐Wei Yao, Yanwei Zhao, Haiyan Shi, Ngaiming Kwok, Xiong Wang, Dexian Huang and Bin Qian and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Cleaner Production.

In The Last Decade

Wanliang Wang

158 papers receiving 2.3k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Wanliang Wang 654 624 416 415 398 166 2.3k
Eneko Osaba 1.3k 1.9× 522 0.8× 231 0.6× 544 1.3× 284 0.7× 108 2.5k
Beatrice Lazzerini 1.3k 2.1× 373 0.6× 319 0.8× 243 0.6× 174 0.4× 183 3.0k
Julio Ortega 1.4k 2.1× 249 0.4× 363 0.9× 347 0.8× 447 1.1× 133 2.5k
Adam Słowik 1.0k 1.6× 199 0.3× 506 1.2× 363 0.9× 305 0.8× 113 2.4k
Salwani Abdullah 1.6k 2.5× 616 1.0× 278 0.7× 412 1.0× 612 1.5× 146 3.2k
Alok Singh 682 1.0× 853 1.4× 298 0.7× 336 0.8× 404 1.0× 101 1.7k
Karam M. Sallam 1.3k 2.1× 250 0.4× 379 0.9× 481 1.2× 408 1.0× 125 2.5k
Christiaan J. J. Paredis 440 0.7× 805 1.3× 208 0.5× 393 0.9× 287 0.7× 171 3.3k
Qifang Luo 1.7k 2.5× 380 0.6× 399 1.0× 663 1.6× 239 0.6× 125 2.7k
Pei‐Wei Tsai 790 1.2× 192 0.3× 397 1.0× 228 0.5× 434 1.1× 90 2.0k

Countries citing papers authored by Wanliang Wang

Since Specialization
Citations

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

Fields of papers citing papers by Wanliang Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wanliang Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Wanliang Wang. A scholar is included among the top collaborators of Wanliang 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 Wanliang Wang. Wanliang Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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2026