Shenglong Zhou

849 total citations
41 papers, 443 citations indexed

About

Shenglong Zhou is a scholar working on Computational Mechanics, Numerical Analysis and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shenglong Zhou has authored 41 papers receiving a total of 443 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computational Mechanics, 11 papers in Numerical Analysis and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shenglong Zhou's work include Sparse and Compressive Sensing Techniques (21 papers), Advanced Optimization Algorithms Research (11 papers) and Indoor and Outdoor Localization Technologies (5 papers). Shenglong Zhou is often cited by papers focused on Sparse and Compressive Sensing Techniques (21 papers), Advanced Optimization Algorithms Research (11 papers) and Indoor and Outdoor Localization Technologies (5 papers). Shenglong Zhou collaborates with scholars based in China, United Kingdom and Poland. Shenglong Zhou's co-authors include Naihua Xiu, Geoffrey Ye Li, Huajun Wang, Yuan‐Hai Shao, Houduo Qi, Alain B. Zemkoho, Lingchen Kong, Rui Wang, Ziyan Luo and Andreas Fischer and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Shenglong Zhou

36 papers receiving 436 citations

Peers

Shenglong Zhou

CVPR

Gaetano Zanghirati Italy

Mert Pilancı United States

Zhaoran Wang United States

Elias S. Helou Brazil

Boujemâa Achchab Morocco

Liang Ge China

Qiuwei Li United States

Yuling Jiao China

Venkat Chandrasekaran United States

Gaetano Zanghirati Italy

Shenglong Zhou

169 ×1.2

151 ×1.3

162 ×1.5

CVPR

123 ×1.8

75 ×1.4

Citations per year, relative to Shenglong Zhou Shenglong Zhou (= 1×) peers Gaetano Zanghirati

Countries citing papers authored by Shenglong Zhou

Since Specialization

Citations

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

Fields of papers citing papers by Shenglong Zhou

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shenglong Zhou

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

All Works

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20 of 20 papers shown

Zhou, Shenglong, et al.. (2024). A step function based recursion method for 0/1 deep neural networks. Applied Mathematics and Computation. 488. 129129–129129. 1 indexed citations

Zhou, Shenglong. (2024). Progress and Applications of Fully Homomorphic Encryption. 6. 55–63.

Zhou, Shenglong, Kaidi Xu, & Geoffrey Ye Li. (2024). Communication-Efficient Decentralized Federated Learning via One-Bit Compressive Sensing. 1–5.

Xu, Kaidi, Shenglong Zhou, & Geoffrey Ye Li. (2024). Federated Reinforcement Learning for Resource Allocation in V2X Networks. 1–5. 7 indexed citations

Xu, Kaidi, Shenglong Zhou, & Geoffrey Ye Li. (2024). Rescale-Invariant Federated Reinforcement Learning for Resource Allocation in V2X Networks. IEEE Communications Letters. 28(12). 2799–2803. 1 indexed citations

Xu, Kaidi, Shenglong Zhou, & Geoffrey Ye Li. (2024). Federated Reinforcement Learning for Resource Allocation in V2X Networks. IEEE Journal of Selected Topics in Signal Processing. 18(7). 1210–1221. 4 indexed citations

Zhou, Shenglong, et al.. (2024). A 0/1 Constrained Optimization Solving Sample Average Approximation for Chance Constrained Programming. Mathematics of Operations Research. 50(4). 2688–2716.

Cao, Jie, Xiaoyu Luo, Shenglong Zhou, et al.. (2023). Isoindigo–Thiophene D–A–D–Type Conjugated Polymers: Electrosynthesis and Electrochromic Performances. International Journal of Molecular Sciences. 24(3). 2219–2219. 6 indexed citations

Wei, Xinyu, et al.. (2023). Accretionary Learning With Deep Neural Networks With Applications. IEEE Transactions on Cognitive Communications and Networking. 10(2). 660–673. 1 indexed citations

10.

Zhou, Shenglong, et al.. (2023). Effective Adaptation into New Environment with Few Shots: Applications to OFDM Receiver Design. 1–6.

11.

Yao, Mingde, Jie Huang, Xin Jin, et al.. (2023). Generalized Lightness Adaptation with Channel Selective Normalization. 10634–10645. 11 indexed citations

12.

Wang, Huajun, et al.. (2021). Support Vector Machine Classifier via Soft-Margin Loss. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(10). 7253–7265. 89 indexed citations

13.

Wang, Rui, Naihua Xiu, & Shenglong Zhou. (2021). An extended Newton-type algorithm for ℓ 2 -regularized sparse logistic regression and its efficiency for classifying large-scale datasets. Journal of Computational and Applied Mathematics. 397. 113656–113656. 13 indexed citations

14.

Zhou, Shenglong, et al.. (2021). Quadratic Convergence of Smoothing Newton's Method for 0/1 Loss Optimization. SIAM Journal on Optimization. 31(4). 3184–3211. 14 indexed citations

15.

Xiu, Naihua, et al.. (2019). Matrix Optimization Over Low-Rank Spectral Sets: Stationary Points and Local and Global Minimizers. Journal of Optimization Theory and Applications. 184(3). 895–930. 4 indexed citations

16.

Wang, Rui, Naihua Xiu, & Shenglong Zhou. (2019). Fast Newton Method for Sparse Logistic Regression. ePrints Soton (University of Southampton). 1 indexed citations

17.

Zhou, Shenglong, Naihua Xiu, & Houduo Qi. (2018). A Fast Matrix Majorization-Projection Method for Penalized Stress Minimization With Box Constraints. IEEE Transactions on Signal Processing. 66(16). 4331–4346. 17 indexed citations

18.

Qin, Yue, Mi Li, Shenglong Zhou, et al.. (2017). SPI-2/CrmA inhibits IFN-β induction by targeting TBK1/IKKε. Scientific Reports. 7(1). 10495–10495. 8 indexed citations

19.

Zhang, Lianjun, Lingchen Kong, Yan Li, & Shenglong Zhou. (2016). A smoothing iterative method for quantile regression with nonconvex <inline-formula><tex-math id="M485">\begin{document}$ \ell_p $\end{document}</tex-math></inline-formula> penalty. Journal of Industrial and Management Optimization. 13(1). 93–112. 5 indexed citations

20.

Shang, Meijuan, Shenglong Zhou, & Naihua Xiu. (2015). Extragradient thresholding methods for sparse solutions of co-coercive NCPs. Journal of Inequalities and Applications. 2015(1). 4 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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