Chen Huang

3.7k total citations · 1 hit paper
25 papers, 1.9k citations indexed

About

Chen Huang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Chen Huang has authored 25 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 3 papers in Computational Mechanics. Recurrent topics in Chen Huang's work include Domain Adaptation and Few-Shot Learning (6 papers), Face recognition and analysis (5 papers) and Video Surveillance and Tracking Methods (5 papers). Chen Huang is often cited by papers focused on Domain Adaptation and Few-Shot Learning (6 papers), Face recognition and analysis (5 papers) and Video Surveillance and Tracking Methods (5 papers). Chen Huang collaborates with scholars based in China, Hong Kong and United States. Chen Huang's co-authors include Chen Change Loy, Xiaoou Tang, Yining Li, Simon Lucey, Deva Ramanan, Yining Li, Hamed Kiani Galoogahi, Ashton Fagg, Yuhang Zang and Minfeng Zhu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, RSC Advances and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Chen Huang

20 papers receiving 1.8k citations

Hit Papers

Learning Deep Representation for Imbalanced Classification 2016 2026 2019 2022 2016 200 400 600
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. Learning Deep Representation for Imbalanced Classification
    2016 627 citations Chen Huang, Yining 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
Chen Huang China 15 1.2k 725 133 125 116 25 1.9k
Yun Xiao China 14 829 0.7× 675 0.9× 133 1.0× 85 0.7× 176 1.5× 60 1.8k
Weihua Ou China 25 1.3k 1.1× 720 1.0× 110 0.8× 98 0.8× 72 0.6× 121 2.1k
Xinchen Yan United States 9 1.1k 1.0× 615 0.8× 74 0.6× 86 0.7× 154 1.3× 14 2.0k
Qiang Guo China 21 706 0.6× 198 0.3× 128 1.0× 104 0.8× 56 0.5× 113 1.5k
Yu Wu China 26 2.7k 2.3× 723 1.0× 68 0.5× 225 1.8× 69 0.6× 109 3.7k
Xiaoliang Dai United States 17 1.4k 1.2× 1.1k 1.5× 287 2.2× 84 0.7× 82 0.7× 44 2.0k
Lucia Maddalena Italy 17 1.2k 1.1× 255 0.4× 96 0.7× 26 0.2× 103 0.9× 56 1.7k
Xin Jin China 23 1.1k 1.0× 345 0.5× 68 0.5× 64 0.5× 52 0.4× 166 1.7k
Xinge You China 21 907 0.8× 355 0.5× 93 0.7× 24 0.2× 110 0.9× 52 1.3k

Countries citing papers authored by Chen Huang

Since Specialization
Citations

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

Fields of papers citing papers by Chen Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chen Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Chen Huang. A scholar is included among the top collaborators of Chen Huang 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 Chen Huang. Chen Huang 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.
Chen, H. S., Hongyu Huang, Xiaojun Fang, et al.. (2025). Machine learning prediction and interpretability analysis of high-risk chest pain: a study from the MIMIC-IV database. Frontiers in Physiology. 16. 1594277–1594277.
2.
Chen, Jun, et al.. (2025). Development of an explainable machine learning model for predicting device-related pressure injuries in clinical settings. BMC Medical Informatics and Decision Making. 25(1). 256–256.
3.
Huang, Chen, et al.. (2025). MPDCGA: a real-coded multi-population dynamic competitive genetic algorithm for feature selection. Journal of King Saud University - Computer and Information Sciences. 37(7).
4.
5.
6.
Huang, Chen, et al.. (2021). Mask-aware photorealistic facial attribute manipulation. Computational Visual Media. 7(3). 363–374. 14 indexed citations
7.
Yan, Chunsheng, et al.. (2021). Analysis of handmade paper by Raman spectroscopy combined with machine learning. Journal of Raman Spectroscopy. 53(2). 260–271. 9 indexed citations
8.
Zang, Yuhang, Chen Huang, & Chen Change Loy. (2021). FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 3437–3446. 74 indexed citations
9.
Huang, Chen, Yining Li, Chen Change Loy, & Xiaoou Tang. (2019). Deep Imbalanced Learning for Face Recognition and Attribute Prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence. 42(11). 2781–2794. 220 indexed citations
10.
Li, Yining, Chen Huang, & Chen Change Loy. (2019). Dense Intrinsic Appearance Flow for Human Pose Transfer. 3688–3697. 127 indexed citations
11.
12.
Huang, Chen, Chen Change Loy, & Xiaoou Tang. (2017). Discriminative Sparse Neighbor Approximation for Imbalanced Learning. IEEE Transactions on Neural Networks and Learning Systems. 29(5). 1503–1513. 23 indexed citations
13.
Wang, Ningning, Chen Huang, Jie Dong, et al.. (2017). ADME properties evaluation in drug discovery: Prediction of plasma protein binding using NSGA-II combining PLS and consensus modeling. Chemometrics and Intelligent Laboratory Systems. 170. 84–95. 27 indexed citations
14.
15.
Li, Yining, Chen Huang, Xiaoou Tang, & Chen Change Loy. (2017). Learning to Disambiguate by Asking Discriminative Questions. 3439–3448. 6 indexed citations
16.
Galoogahi, Hamed Kiani, Ashton Fagg, Chen Huang, Deva Ramanan, & Simon Lucey. (2017). Need for Speed: A Benchmark for Higher Frame Rate Object Tracking. 1134–1143. 323 indexed citations
17.
Huang, Chen, Chen Change Loy, & Xiaoou Tang. (2016). Local similarity-aware deep feature embedding. Neural Information Processing Systems. 29. 1270–1278. 46 indexed citations
18.
Huang, Chen, Chen Change Loy, & Xiaoou Tang. (2016). Unsupervised Learning of Discriminative Attributes and Visual Representations. 5175–5184. 66 indexed citations
19.
Huang, Chen, Yining Li, Chen Change Loy, & Xiaoou Tang. (2016). Learning Deep Representation for Imbalanced Classification. 5375–5384. 627 indexed citations breakdown →
20.
Huang, Chen, Jian Zhu, Hanqiu Sun, & Enhua Wu. (2013). Parallel‐optimizing SPH fluid simulation for realistic VR environments. Computer Animation and Virtual Worlds. 26(1). 43–54. 5 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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