Ran Wang

3.3k total citations · 2 hit papers
88 papers, 2.4k citations indexed

About

Ran Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Ran Wang has authored 88 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Artificial Intelligence, 34 papers in Computer Vision and Pattern Recognition and 10 papers in Computational Theory and Mathematics. Recurrent topics in Ran Wang's work include Machine Learning and ELM (25 papers), Face and Expression Recognition (20 papers) and Text and Document Classification Technologies (14 papers). Ran Wang is often cited by papers focused on Machine Learning and ELM (25 papers), Face and Expression Recognition (20 papers) and Text and Document Classification Technologies (14 papers). Ran Wang collaborates with scholars based in China, Hong Kong and Australia. Ran Wang's co-authors include Sam Kwong, Xizhao Wang, Ke Li, Farhad Pourpanah, Chee Peng Lim, Qingfu Zhang, Miqing Li, Yuheng Jia, Jingjing Cao and Xinlei Zhou and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Information Sciences.

In The Last Decade

Ran Wang

84 papers receiving 2.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Stable Matching-Based Selection in Evolutionary Multiobjective Optimization

2014 273 citations Ke Li, Sam Kwong et al. profile →
A Review of Generalized Zero-Shot Learning Methods

2022 239 citations Farhad Pourpanah, Ran Wang et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ran Wang China	28	1.5k	614	485	270	234	88	2.4k
Ahamad Tajudin Khader Malaysia	25	1.7k 1.2×	484 0.8×	544 1.1×	334 1.2×	195 0.8×	66	3.0k
Thomas A. Runkler Germany	24	1.4k 1.0×	418 0.7×	236 0.5×	273 1.0×	339 1.4×	132	2.6k
Jeffrey O. Agushaka South Africa	18	1.5k 1.0×	428 0.7×	530 1.1×	206 0.8×	121 0.5×	27	2.8k
Liangxiao Jiang China	31	2.6k 1.8×	548 0.9×	456 0.9×	772 2.9×	177 0.8×	114	3.6k
Heitor Silvério Lopes Brazil	21	1.6k 1.1×	405 0.7×	361 0.7×	374 1.4×	90 0.4×	148	2.5k
Changjing Shang United Kingdom	26	889 0.6×	492 0.8×	307 0.6×	202 0.7×	162 0.7×	162	2.2k
Ayed Salman Kuwait	16	1.2k 0.8×	402 0.7×	412 0.8×	216 0.8×	79 0.3×	48	2.1k
Siti Mariyam Shamsuddin Malaysia	23	1.2k 0.8×	365 0.6×	228 0.5×	258 1.0×	106 0.5×	133	2.4k
Beatrice Lazzerini Italy	28	1.4k 0.9×	270 0.4×	243 0.5×	236 0.9×	231 1.0×	183	3.0k
Feng Zou China	26	988 0.7×	455 0.7×	569 1.2×	129 0.5×	83 0.4×	127	2.2k

Countries citing papers authored by Ran Wang

Since Specialization

Citations

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

Fields of papers citing papers by Ran Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ran Wang

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Jia, Yuheng, Jianan Li, Wenhui Wu, & Ran Wang. (2024). Semi-Supervised Symmetric Non-Negative Matrix Factorization With Low-Rank Tensor Representation. IEEE Transactions on Circuits and Systems for Video Technology. 35(2). 1534–1547. 2 indexed citations

Zhang, Xinying, Ran Wang, Shuyue Chen, Yuheng Jia, & Debby D. Wang. (2024). AME-LSIFT: Attention-Aware Multi-Label Ensemble With Label Subset-SpecIfic FeaTures. IEEE Transactions on Knowledge and Data Engineering. 36(12). 7627–7642. 1 indexed citations

Chen, Shuyue, et al.. (2023). A meta-framework for multi-label active learning based on deep reinforcement learning. Neural Networks. 162. 258–270. 8 indexed citations

Wang, Ran, Shuyue Chen, & Yu Yu. (2023). Extending version-space theory to multi-label active learning with imbalanced data. Pattern Recognition. 142. 109690–109690. 2 indexed citations

Wang, Ran, et al.. (2023). Adversarially robust neural networks with feature uncertainty learning and label embedding. Neural Networks. 172. 106087–106087. 3 indexed citations

Wang, Ran, et al.. (2022). Contrastive Learning-Enhanced Nearest Neighbor Mechanism for Multi-Label Text Classification. 672–679. 37 indexed citations

Wu, Wenhui, et al.. (2022). No-reference image quality assessment by using convolutional neural networks via object detection. International Journal of Machine Learning and Cybernetics. 13(11). 3543–3554. 4 indexed citations

Chen, Shuyue, et al.. (2022). Stable matching-based two-way selection in multi-label active learning with imbalanced data. Information Sciences. 610. 281–299. 9 indexed citations

Wu, Wenhui, Yujie Chen, Ran Wang, & Le Ou-Yang. (2022). Self-representative kernel concept factorization. Knowledge-Based Systems. 259. 110051–110051. 5 indexed citations

10.

Wu, Wenhui, Yuheng Jia, Shiqi Wang, et al.. (2020). Positive and Negative Label-Driven Nonnegative Matrix Factorization. IEEE Transactions on Circuits and Systems for Video Technology. 31(7). 2698–2710. 25 indexed citations

11.

Lyu, Yan, Chi-Yin Chow, Ran Wang, & Victor C. S. Lee. (2019). iMCRec: A multi-criteria framework for personalized point-of-interest recommendations. Information Sciences. 483. 294–312. 26 indexed citations

12.

Pourpanah, Farhad, et al.. (2019). Feature Selection for Data Classification based on Binary Brain Storm Optimization. 3. 108–113. 4 indexed citations

13.

Wang, Ran, Sam Kwong, Yuheng Jia, Zhiqi Huang, & Lang Wu. (2018). Mutual Information Based K-Labelsets Ensemble for Multi-Label Classification. 1–7. 4 indexed citations

14.

Wang, Ran, Chi-Yin Chow, Yan Lyu, et al.. (2017). TaxiRec: Recommending Road Clusters to Taxi Drivers Using Ranking-Based Extreme Learning Machines. IEEE Transactions on Knowledge and Data Engineering. 30(3). 585–598. 52 indexed citations

15.

Li, Yingjie, Ran Wang, & Simon Shiu. (2015). Interval extreme learning machine for big data based on uncertainty reduction. Journal of Intelligent & Fuzzy Systems. 28(5). 2391–2403. 8 indexed citations

16.

Cao, Jingjing, Sam Kwong, Ran Wang, & Ke Li. (2014). AN indicator-based selection multi-objective evolutionary algorithm with preference for multi-class ensemble. 21. 147–152. 2 indexed citations

17.

Li, Xiaodong, Haoran Xie, Ran Wang, et al.. (2014). Empirical analysis: stock market prediction via extreme learning machine. Neural Computing and Applications. 27(1). 67–78. 114 indexed citations

18.

Wang, Ran, Sam Kwong, & Debby D. Wang. (2013). AN ANALYSIS OF ELM APPROXIMATE ERROR BASED ON RANDOM WEIGHT MATRIX. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems. 21(supp02). 1–12. 7 indexed citations

19.

Wang, Xizhao, et al.. (2013). A New Approach to Classifier Fusion Based on Upper Integral. IEEE Transactions on Cybernetics. 44(5). 620–635. 38 indexed citations

20.

Li, Ke, Sam Kwong, Ran Wang, K.S. Tang, & K.F. Man. (2012). Learning paradigm based on jumping genes: A general framework for enhancing exploration in evolutionary multiobjective optimization. Information Sciences. 226. 1–22. 32 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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