Ao Li

920 total citations · 1 hit paper
64 papers, 543 citations indexed

About

Ao Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Ao Li has authored 64 papers receiving a total of 543 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Computer Vision and Pattern Recognition, 20 papers in Artificial Intelligence and 12 papers in Computational Mechanics. Recurrent topics in Ao Li's work include Face and Expression Recognition (17 papers), Sparse and Compressive Sensing Techniques (9 papers) and Video Surveillance and Tracking Methods (9 papers). Ao Li is often cited by papers focused on Face and Expression Recognition (17 papers), Sparse and Compressive Sensing Techniques (9 papers) and Video Surveillance and Tracking Methods (9 papers). Ao Li collaborates with scholars based in China, United States and Hong Kong. Ao Li's co-authors include Maomao Hu, Cheng Fan, Guanglu Sun, Deyun Chen, Shibiao Xu, Zhiqiang Wu, W. Xu, Shuchen Zheng, Rongtao Xu and Jiguang Zhang and has published in prestigious journals such as PLoS ONE, The Science of The Total Environment and International Journal of Hydrogen Energy.

In The Last Decade

Ao Li

53 papers receiving 535 citations

Hit Papers

HCF-Net: Hierarchical Context Fusion Network for Infrared... 2024 2026 2025 2024 20 40 60
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.

  1. HCF-Net: Hierarchical Context Fusion Network for Infrared Small Object Detection
    2024 71 citations Shibiao Xu, Ao Li et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ao Li China 12 206 140 94 81 61 64 543
Yung-Yao Chen Taiwan 15 364 1.8× 73 0.5× 124 1.3× 68 0.8× 62 1.0× 82 705
Jianwu Dang China 12 332 1.6× 143 1.0× 93 1.0× 21 0.3× 92 1.5× 92 724
Shangbing Gao China 12 302 1.5× 190 1.4× 111 1.2× 19 0.2× 93 1.5× 61 574
Heinz Hertlein United Kingdom 3 553 2.7× 221 1.6× 54 0.6× 43 0.5× 77 1.3× 5 875
Liping Zheng China 13 245 1.2× 71 0.5× 30 0.3× 39 0.5× 47 0.8× 74 477
Liqiang Zhu China 16 152 0.7× 95 0.7× 198 2.1× 36 0.4× 43 0.7× 72 759
Wouter Van Gansbeke Belgium 4 366 1.8× 326 2.3× 53 0.6× 22 0.3× 46 0.8× 6 718
Gaowei Yan China 14 76 0.4× 124 0.9× 146 1.6× 51 0.6× 20 0.3× 72 560
Hongyu Yang China 14 140 0.7× 254 1.8× 51 0.5× 71 0.9× 33 0.5× 57 630
Liquan Zhao China 10 250 1.2× 122 0.9× 92 1.0× 12 0.1× 69 1.1× 50 602

Countries citing papers authored by Ao Li

Since Specialization
Citations

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

Fields of papers citing papers by Ao Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ao Li

This figure shows the co-authorship network connecting the top 25 collaborators of Ao Li. A scholar is included among the top collaborators of Ao Li 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 Ao Li. Ao Li 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
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Li, Ao, et al.. (2025). Deep spectral clustering network for incomplete multi-view clustering. Engineering Applications of Artificial Intelligence. 148. 110387–110387. 1 indexed citations
3.
Li, Ao, et al.. (2025). High-precision humidity calibration for variation of humidity sensitivity in polyimide coated FBG sensors. Optics Communications. 596. 132437–132437.
4.
Ding, Yulong, et al.. (2025). Learning to Discriminate While Contrasting: Combating False Negative Pairs With Coupled Contrastive Learning for Incomplete Multi-View Clustering. IEEE Transactions on Knowledge and Data Engineering. 37(10). 6046–6060.
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Li, Ao, Chong Shi, Shuai Yin, et al.. (2024). Variation of surface solar radiation components from 2016 to 2020 in China: Perspective from geostationary satellite observation with a high spatiotemporal resolution. The Science of The Total Environment. 954. 176264–176264. 3 indexed citations
7.
He, Jingfei, et al.. (2024). Low-rank tensor completion based on tensor train rank with partially overlapped sub-blocks and total variation. Signal Processing Image Communication. 129. 117193–117193.
8.
Li, Ao, et al.. (2024). Incomplete multi-view clustering via local and global bagging of anchor graphs. Expert Systems with Applications. 248. 123402–123402. 9 indexed citations
9.
Li, Ao, et al.. (2024). Deep Incomplete Multiview Clustering via Local and Global Pseudo-Label Propagation. IEEE Transactions on Neural Networks and Learning Systems. 36(5). 8684–8698. 3 indexed citations
10.
Wan, Xinhang, Jiyuan Liu, Hao Yu, et al.. (2024). Contrastive Continual Multiview Clustering With Filtered Structural Fusion. IEEE Transactions on Neural Networks and Learning Systems. 36(8). 14829–14842. 6 indexed citations
11.
Wang, Ze, et al.. (2024). Traffic Flow Prediction Using Novel Spatial-Temporal Multi-Head Attention Graph Convolution Networks. Transportation Research Record Journal of the Transportation Research Board. 2679(3). 883–898. 1 indexed citations
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Li, Ao, et al.. (2023). Optimizing micro-diffusion flame energy density and stability through the application of magnetic fields: A numerical study. International Journal of Hydrogen Energy. 51. 179–189. 6 indexed citations
14.
Li, Ao, et al.. (2023). Graph t-SNE multi-view autoencoder for joint clustering and completion of incomplete multi-view data. Knowledge-Based Systems. 284. 111324–111324. 16 indexed citations
15.
Tang, Zhi‐Ri, Kam-Yiu Lam, Chi-Yin Chow, et al.. (2023). Weakly supervised real-time instance segmentation for ultrasound images of median nerves. Computers in Biology and Medicine. 162. 107057–107057. 6 indexed citations
16.
Li, Ao, et al.. (2023). Incomplete multiview subspace clustering based on multiple kernel low-redundant representation learning. Information Fusion. 103. 102086–102086. 26 indexed citations
17.
Xi, Liang, et al.. (2022). Unsupervised dimension-contribution-aware embeddings transformation for anomaly detection. Knowledge-Based Systems. 262. 110209–110209. 10 indexed citations
18.
Xi, Liang, et al.. (2022). Unsupervised multimodal domain adversarial network for time series classification. Information Sciences. 624. 147–164. 13 indexed citations
19.
Bai, Jing‐Xuan, et al.. (2019). Small Object Detection Algorithm Based on Feature Pyramid‐Enhanced Fusion SSD. Complexity. 2019(1). 11 indexed citations
20.

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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