Hengrong Ju

927 total citations
53 papers, 648 citations indexed

About

Hengrong Ju is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems. According to data from OpenAlex, Hengrong Ju has authored 53 papers receiving a total of 648 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 27 papers in Computational Theory and Mathematics and 16 papers in Information Systems. Recurrent topics in Hengrong Ju's work include Rough Sets and Fuzzy Logic (27 papers), Data Mining Algorithms and Applications (14 papers) and Text and Document Classification Technologies (8 papers). Hengrong Ju is often cited by papers focused on Rough Sets and Fuzzy Logic (27 papers), Data Mining Algorithms and Applications (14 papers) and Text and Document Classification Technologies (8 papers). Hengrong Ju collaborates with scholars based in China, Canada and Macao. Hengrong Ju's co-authors include Xibei Yang, Weiping Ding, Jiashuang Huang, Witold Pedrycz, Huaxiong Li, Xianzhong Zhou, Suping Xu, Chin‐Teng Lin, Keyu Liu and Bing Huang and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.

In The Last Decade

Hengrong Ju

43 papers receiving 639 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hengrong Ju China 14 405 351 220 179 76 53 648
G. Jothi India 11 174 0.4× 332 0.9× 104 0.5× 211 1.2× 27 0.4× 20 629
Gurdial Arora United States 4 179 0.4× 140 0.4× 85 0.4× 241 1.3× 78 1.0× 6 495
Jin-Seon Lee South Korea 4 123 0.3× 469 1.3× 66 0.3× 227 1.3× 23 0.3× 10 760
Yanyong Huang China 14 407 1.0× 378 1.1× 250 1.1× 171 1.0× 154 2.0× 26 750
Guoqiu Wen China 13 79 0.2× 306 0.9× 45 0.2× 221 1.2× 105 1.4× 40 550
Jinjie Huang China 11 62 0.2× 307 0.9× 46 0.2× 138 0.8× 15 0.2× 43 565
Shangzhu Jin China 12 87 0.2× 228 0.6× 43 0.2× 142 0.8× 42 0.6× 57 427
Eghbal G. Mansoori Iran 12 104 0.3× 356 1.0× 74 0.3× 120 0.7× 41 0.5× 50 571
Ken Nozaki Japan 5 205 0.5× 727 2.1× 91 0.4× 61 0.3× 128 1.7× 9 863
Manish Sarkar United States 8 96 0.2× 209 0.6× 76 0.3× 80 0.4× 21 0.3× 12 326

Countries citing papers authored by Hengrong Ju

Since Specialization
Citations

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

Fields of papers citing papers by Hengrong Ju

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hengrong Ju

This figure shows the co-authorship network connecting the top 25 collaborators of Hengrong Ju. A scholar is included among the top collaborators of Hengrong Ju 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 Hengrong Ju. Hengrong Ju 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.
Xu, Suping, Lin Shang, Keyu Liu, et al.. (2025). Margin-Aware Fuzzy Rough Feature Selection: Bridging Uncertainty Characterization and Pattern Classification. IEEE Transactions on Fuzzy Systems. 34(1). 138–151.
2.
Wang, Haipeng, et al.. (2025). F2CAU-Net: A dual fuzzy medical image segmentation cascade method based on fuzzy feature learning. Applied Soft Computing. 184. 113692–113692.
3.
Huang, Jiashuang, Mingliang Wang, Hengrong Ju, Weiping Ding, & Daoqiang Zhang. (2024). AGBN-Transformer: Anatomy-guided brain network transformer for schizophrenia diagnosis. Biomedical Signal Processing and Control. 102. 107226–107226.
4.
Ju, Hengrong, et al.. (2024). D3WC: Deep three-way clustering with granular evidence fusion. Information Fusion. 114. 102699–102699. 4 indexed citations
5.
Ding, Weiping, et al.. (2024). Quality-aware fuzzy min–max neural networks for dynamic brain network analysis and its application to schizophrenia identification. Applied Soft Computing. 169. 112538–112538. 2 indexed citations
6.
Ding, Weiping, et al.. (2024). FDBFN: Fuzzy discriminative broad fusion network for hyperspectral image classification. Expert Systems with Applications. 266. 126026–126026. 2 indexed citations
7.
Chu, Yonghe, et al.. (2024). Hyperspectral image classification using feature fusion fuzzy graph broad network. Information Sciences. 689. 121504–121504. 6 indexed citations
8.
Ju, Hengrong, Weiping Ding, Keyu Liu, et al.. (2024). BiFuG2-Spark: Bi-Directional Fuzzy Granular-Cabin Parallel Attribute Reduction Accelerator With Granular-Group Collaboration. IEEE Transactions on Fuzzy Systems. 32(8). 4234–4247. 4 indexed citations
9.
Ju, Hengrong, Weiping Ding, Jiashuang Huang, et al.. (2024). Dual-Channel Fuzzy Interaction Information Fused Feature Selection With Fuzzy Sparse and Shared Granularities. IEEE Transactions on Fuzzy Systems. 32(11). 6056–6068. 4 indexed citations
10.
Chen, Yuepeng, et al.. (2024). Cascaded Two-Stage Feature Clustering and Selection via Separability and Consistency in Fuzzy Decision Systems. IEEE Transactions on Fuzzy Systems. 32(9). 5320–5333. 3 indexed citations
11.
Ju, Hengrong, et al.. (2024). Multi-association evidential feature selection and its application to identifying schizophrenia. Information Sciences. 674. 120647–120647. 2 indexed citations
12.
Ding, Weiping, et al.. (2024). ELSNC: A semi-supervised community detection method with integration of embedding-enhanced links and node content in attributed networks. Applied Soft Computing. 167. 112250–112250. 1 indexed citations
13.
Ju, Hengrong, et al.. (2023). Three-way evidence theory-based density peak clustering with the principle of justifiable granularity. Applied Soft Computing. 152. 111217–111217. 13 indexed citations
14.
Ding, Weiping, Haipeng Wang, Jiashuang Huang, et al.. (2023). FTransCNN: Fusing Transformer and a CNN based on fuzzy logic for uncertain medical image segmentation. Information Fusion. 99. 101880–101880. 65 indexed citations
15.
Ding, Weiping, et al.. (2023). ViTH-RFG: Vision Transformer Hashing With Residual Fuzzy Generation for Targeted Attack in Medical Image Retrieval. IEEE Transactions on Fuzzy Systems. 32(10). 5571–5584. 5 indexed citations
16.
Zhang, Jiadong, Keyu Liu, Xibei Yang, Hengrong Ju, & Suping Xu. (2023). Multi-label learning with Relief-based label-specific feature selection. Applied Intelligence. 53(15). 18517–18530. 10 indexed citations
17.
Liu, Keyu, Tianrui Li, Xibei Yang, et al.. (2023). Feature selection in threes: Neighborhood relevancy, redundancy, and granularity interactivity. Applied Soft Computing. 146. 110679–110679. 19 indexed citations
18.
Ding, Weiping, Ying Sun, Jiashuang Huang, et al.. (2023). RCAR-UNet: Retinal vessel segmentation network algorithm via novel rough attention mechanism. Information Sciences. 657. 120007–120007. 27 indexed citations
19.
Ju, Hengrong, Weiping Ding, Xibei Yang, Hamido Fujita, & Suping Xu. (2021). Robust supervised rough granular description model with the principle of justifiable granularity. Applied Soft Computing. 110. 107612–107612. 38 indexed citations
20.
Xu, Suping, et al.. (2020). Label distribution learning: A local collaborative mechanism. International Journal of Approximate Reasoning. 121. 59–84. 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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