Benyun Shi

1.3k total citations
74 papers, 807 citations indexed

About

Benyun Shi is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Modeling and Simulation. According to data from OpenAlex, Benyun Shi has authored 74 papers receiving a total of 807 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Statistical and Nonlinear Physics, 17 papers in Artificial Intelligence and 17 papers in Modeling and Simulation. Recurrent topics in Benyun Shi's work include COVID-19 epidemiological studies (17 papers), Complex Network Analysis Techniques (14 papers) and Opinion Dynamics and Social Influence (12 papers). Benyun Shi is often cited by papers focused on COVID-19 epidemiological studies (17 papers), Complex Network Analysis Techniques (14 papers) and Opinion Dynamics and Social Influence (12 papers). Benyun Shi collaborates with scholars based in China, Hong Kong and United States. Benyun Shi's co-authors include Jiming Liu, Kwang Mong Sim, Shang Xia, Xiao‐Nong Zhou, Yuanyuan Guo, Yizhi Ren, Yong Shi, Liu Yang, Guanghu Zhu and Guo-Jing Yang and has published in prestigious journals such as PLoS ONE, Langmuir and Scientific Reports.

In The Last Decade

Benyun Shi

68 papers receiving 788 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Benyun Shi China 16 193 160 154 113 99 74 807
Samarth Swarup United States 16 170 0.9× 48 0.3× 194 1.3× 239 2.1× 129 1.3× 89 976
Armin R. Mikler United States 12 127 0.7× 84 0.5× 94 0.6× 126 1.1× 180 1.8× 73 666
Adam Sadilek United States 17 262 1.4× 56 0.3× 336 2.2× 150 1.3× 255 2.6× 31 1.4k
Jiangzhuo Chen United States 18 490 2.5× 82 0.5× 175 1.1× 63 0.6× 321 3.2× 69 1.1k
Mahendra Piraveenan Australia 17 166 0.9× 113 0.7× 75 0.5× 163 1.4× 69 0.7× 57 1.0k
Ceyhun Eksin United States 12 203 1.1× 172 1.1× 42 0.3× 246 2.2× 32 0.3× 51 706
Adiqa Kausar Kiani Pakistan 20 190 1.0× 78 0.5× 174 1.1× 39 0.3× 36 0.4× 98 1.1k
Lucía Russo Italy 11 550 2.8× 102 0.6× 74 0.5× 55 0.5× 119 1.2× 22 1.2k
Marco Quaggiotto Italy 5 222 1.2× 51 0.3× 88 0.6× 74 0.7× 110 1.1× 5 718
Pritha Das India 22 318 1.6× 320 2.0× 76 0.5× 59 0.5× 20 0.2× 122 1.5k

Countries citing papers authored by Benyun Shi

Since Specialization
Citations

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

Fields of papers citing papers by Benyun Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Benyun Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Benyun Shi. A scholar is included among the top collaborators of Benyun Shi 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 Benyun Shi. Benyun Shi 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.
Shi, Benyun, et al.. (2025). Hollow InVO 4 Microspheres toward Promoting Photocatalytic CO 2 Conversion Performance. Langmuir. 41(48). 32770–32776.
2.
Liu, Feng, et al.. (2025). Toward a physics-guided machine learning approach for predicting chaotic systems dynamics. Frontiers in Big Data. 7. 1506443–1506443. 1 indexed citations
3.
He, Hailun, et al.. (2024). Forecasting sea surface temperature during typhoon events in the Bohai Sea using spatiotemporal neural networks. Atmospheric Research. 309. 107578–107578. 8 indexed citations
4.
Shi, Benyun, et al.. (2024). An Attention-Based Context Fusion Network for Spatiotemporal Prediction of Sea Surface Temperature. IEEE Geoscience and Remote Sensing Letters. 21. 1–5. 9 indexed citations
5.
Xia, Ji-Wen, et al.. (2024). Information-guided adaptive learning approach for active surveillance of infectious diseases. Infectious Disease Modelling. 10(1). 257–267. 1 indexed citations
6.
Shi, Benyun, et al.. (2024). Sea Surface Temperature Prediction Using ConvLSTM-Based Model with Deformable Attention. Remote Sensing. 16(22). 4126–4126. 9 indexed citations
7.
8.
Zheng, Jinxin, Benyun Shi, Shang Xia, Guo-Jing Yang, & Xiao‐Nong Zhou. (2021). Spatial patterns of <em>Plasmodium vivax</em> transmission explored by multivariate auto-regressive state-space modelling - A case study in Baoshan Prefecture in southern China. Geospatial health. 16(1). 1 indexed citations
9.
Yang, Liu, Shang Xia, Benyun Shi, et al.. (2020). What are the underlying transmission patterns of COVID-19 outbreak? An age-specific social contact characterization. EClinicalMedicine. 22. 100354–100354. 110 indexed citations
10.
Liu, Yang, et al.. (2020). Heterogeneous neural metric learning for spatio-temporal modeling of infectious diseases with incomplete data. Neurocomputing. 458. 701–713. 3 indexed citations
11.
Shi, Benyun, Shan Lin, Jie Cao, et al.. (2020). Inference and prediction of malaria transmission dynamics using time series data. Infectious Diseases of Poverty. 9(1). 95–95. 11 indexed citations
12.
Ke, Hengjin, Dan Chen, Benyun Shi, et al.. (2019). Improving Brain E-Health Services via High-Performance EEG Classification With Grouping Bayesian Optimization. IEEE Transactions on Services Computing. 13(4). 696–708. 58 indexed citations
13.
Liu, Rui, et al.. (2018). cmFSM: a scalable CPU-MIC coordinated drug-finding tool by frequent subgraph mining. BMC Bioinformatics. 19(S4). 98–98. 5 indexed citations
14.
Chen, Dan, et al.. (2017). Comprehensive Association Rules Mining of Health Examination Data with an Extended FP-Growth Method. Mobile Networks and Applications. 22(2). 267–274. 22 indexed citations
15.
Chen, Dan, Jun Chen, Jingying Chen, et al.. (2017). Person re-identification with multiple similarity probabilities using deep metric learning for efficient smart security applications. Journal of Parallel and Distributed Computing. 132. 230–241. 9 indexed citations
16.
Zhu, Guanghu, et al.. (2016). Inferring the Spatio-temporal Patterns of Dengue Transmission from Surveillance Data in Guangzhou, China. PLoS neglected tropical diseases. 10(4). e0004633–e0004633. 40 indexed citations
17.
Shi, Benyun, et al.. (2014). Forecasting disease incidences using state space model. HKBU Institutional Repository (Hong Kong Baptist University). 2 indexed citations
18.
Wiwanitkit, Viroj, et al.. (2013). Research priorities in modeling the transmission risks of H7N9 bird flu. Infectious Diseases of Poverty. 2(1). 17–17. 13 indexed citations
19.
Shi, Benyun & Jiming Liu. (2012). A Decentralized Mechanism for Improving the Functional Robustness of Distribution Networks. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 42(5). 1369–1382. 4 indexed citations
20.
Deng, Xiaotie, Haodi Feng, Guojun Li, & Benyun Shi. (2005). A PTAS for Semiconductor Burn-in Scheduling. Journal of Combinatorial Optimization. 9(1). 5–17. 20 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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