Ju Sun

6.1k total citations · 1 hit paper
71 papers, 4.0k citations indexed

About

Ju Sun is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiation. According to data from OpenAlex, Ju Sun has authored 71 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 13 papers in Computer Vision and Pattern Recognition and 12 papers in Radiation. Recurrent topics in Ju Sun's work include Advanced X-ray Imaging Techniques (12 papers), Sparse and Compressive Sensing Techniques (8 papers) and Advanced Electron Microscopy Techniques and Applications (5 papers). Ju Sun is often cited by papers focused on Advanced X-ray Imaging Techniques (12 papers), Sparse and Compressive Sensing Techniques (8 papers) and Advanced Electron Microscopy Techniques and Applications (5 papers). Ju Sun collaborates with scholars based in United States, China and Singapore. Ju Sun's co-authors include Shuicheng Yan, Guangcan Liu, Yi Ma, Yong Yu, Zhouchen Lin, John Wright, Qing Qu, Loong‐Fah Cheong, Tat‐Seng Chua and Xiao Wu and has published in prestigious journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Information Theory.

In The Last Decade

Ju Sun

67 papers receiving 3.9k citations

Hit Papers

Robust Recovery of Subspace Structures by Low-Rank Repres... 2012 2026 2016 2021 2012 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ju Sun United States 18 2.6k 1.2k 1.1k 943 353 71 4.0k
Ehsan Elhamifar United States 20 3.2k 1.2× 1.2k 1.0× 1.7k 1.5× 1.1k 1.1× 462 1.3× 50 4.4k
Francis Bach France 15 3.9k 1.5× 1.8k 1.5× 1.2k 1.1× 1.3k 1.4× 867 2.5× 23 6.1k
Guangcan Liu China 30 5.3k 2.1× 2.6k 2.1× 1.9k 1.7× 2.1k 2.2× 684 1.9× 107 7.1k
Xiangchu Feng China 25 6.7k 2.6× 2.3k 1.9× 986 0.9× 3.2k 3.4× 779 2.2× 158 8.3k
Lunke Fei China 36 4.1k 1.6× 361 0.3× 1.5k 1.3× 1.2k 1.3× 1.4k 4.1× 116 5.5k
Chao Xu China 32 3.9k 1.5× 287 0.2× 2.2k 1.9× 969 1.0× 248 0.7× 131 5.4k
Lihi Zelnik‐Manor Israel 27 5.0k 1.9× 331 0.3× 1.4k 1.3× 687 0.7× 382 1.1× 57 6.2k
Qian Zhao China 34 3.4k 1.3× 911 0.7× 767 0.7× 1.9k 2.1× 253 0.7× 124 4.8k
Shuhang Gu China 26 5.9k 2.3× 1.3k 1.0× 405 0.4× 3.1k 3.3× 346 1.0× 54 6.8k
Jianzhuang Liu China 43 6.2k 2.4× 393 0.3× 1.6k 1.5× 1.5k 1.5× 591 1.7× 204 7.6k

Countries citing papers authored by Ju Sun

Since Specialization
Citations

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

Fields of papers citing papers by Ju Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ju Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Ju Sun. A scholar is included among the top collaborators of Ju Sun 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 Ju Sun. Ju Sun 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.
Zhou, Jun, Guangming Zhao, Xiangrui Meng, et al.. (2025). Dynamic characteristics and fracture morphology of two rocks with different length to diameter ratios. 44(9). 2379–2390. 1 indexed citations
2.
Zhang, Cheng, Yan Li, Ning Zhang, et al.. (2025). Dynamic adaptation mutations and pathogenic characterization of a mouse-adapted seasonal human H3N2 influenza virus. Virology Journal. 22(1). 223–223.
3.
Naik, Anant, et al.. (2025). Automated ventricular segmentation in pediatric hydrocephalus: how close are we?. Journal of Neurosurgery Pediatrics. 36(2). 165–172.
4.
Yang, Jing, Shufa Zheng, Ju Sun, et al.. (2025). A human-infecting H10N5 avian influenza virus: Clinical features, virus reassortment, receptor-binding affinity, and possible transmission routes. Journal of Infection. 90(4). 106456–106456. 4 indexed citations
5.
Wang, Wenjie, Shan Liu, Ji Pei, Ju Sun, & Qin Sun. (2024). Efficiency improvement and pressure pulsation reduction of volute centrifugal pump through diffuser design optimization. Journal of Energy Storage. 102. 114184–114184. 10 indexed citations
6.
Han, Lu, et al.. (2024). Interpretable deep learning methods for multiview learning. BMC Bioinformatics. 25(1). 69–69. 6 indexed citations
7.
Xu, Lin, Ju Sun, Yanjun Wang, et al.. (2024). Five-year longitudinal surveillance reveals the continual circulation of both alpha- and beta-coronaviruses in Plateau and Gansu pikas ( Ochotona spp.) at Qinghai Lake, China 1. Emerging Microbes & Infections. 13(1). 2392693–2392693. 3 indexed citations
9.
Sun, Ju, Tianyi Zheng, Mingjun Jia, et al.. (2024). Dual receptor-binding, infectivity, and transmissibility of an emerging H2N2 low pathogenicity avian influenza virus. Nature Communications. 15(1). 10012–10012. 3 indexed citations
10.
Yang, David J., et al.. (2023). Practical phase retrieval using double deep image priors. Electronic Imaging. 35(14). 153–1. 5 indexed citations
11.
Zhou, Sicheng, Nan Wang, Liwei Wang, et al.. (2023). A cross-institutional evaluation on breast cancer phenotyping NLP algorithms on electronic health records. Computational and Structural Biotechnology Journal. 22. 32–40. 8 indexed citations
12.
Shen, Li, et al.. (2023). A Unified Analysis of AdaGrad With Weighted Aggregation and Momentum Acceleration. IEEE Transactions on Neural Networks and Learning Systems. 35(10). 14482–14490. 14 indexed citations
13.
Sun, Ju, Genevieve B. Melton, Nicholas E. Ingraham, et al.. (2022). Performance of a Chest Radiograph AI Diagnostic Tool for COVID-19: A Prospective Observational Study. Radiology Artificial Intelligence. 4(4). e210217–e210217. 23 indexed citations
14.
Yang, Jing, Yuhuan Gong, Ju Sun, et al.. (2022). Co-existence and co-infection of influenza A viruses and coronaviruses: Public health challenges. The Innovation. 3(5). 100306–100306. 37 indexed citations
15.
Kumar, Vipin, et al.. (2020). End to End learning for Phase Retrieval. International Conference on Machine Learning. 2 indexed citations
16.
Sun, Ju, et al.. (2019). Holographic phase retrieval and reference design. Inverse Problems. 35(9). 94001–94001. 22 indexed citations
17.
Bai, Yu, et al.. (2018). Subgradient Descent Learns Orthogonal Dictionaries. arXiv (Cornell University). 13 indexed citations
18.
Sun, Ju, Qing Qu, & John Wright. (2015). Complete Dictionary Recovery Using Nonconvex Optimization. International Conference on Machine Learning. 2351–2360. 16 indexed citations
19.
Sun, Ju, Xiao Wu, Shuicheng Yan, et al.. (2009). Hierarchical spatio-temporal context modeling for action recognition. 2009 IEEE Conference on Computer Vision and Pattern Recognition. 2004–2011. 245 indexed citations
20.
Sun, Ju, et al.. (2003). Job shop scheduling with sequence dependent setup times to minimize makespan. International journal of industrial engineering. 10(4). 455–461. 7 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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