Shi Ying

680 total citations
33 papers, 484 citations indexed

About

Shi Ying is a scholar working on Artificial Intelligence, Information Systems and Software. According to data from OpenAlex, Shi Ying has authored 33 papers receiving a total of 484 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 19 papers in Information Systems and 8 papers in Software. Recurrent topics in Shi Ying's work include Software Engineering Research (16 papers), Advanced Software Engineering Methodologies (10 papers) and Software Reliability and Analysis Research (7 papers). Shi Ying is often cited by papers focused on Software Engineering Research (16 papers), Advanced Software Engineering Methodologies (10 papers) and Software Reliability and Analysis Research (7 papers). Shi Ying collaborates with scholars based in China, Australia and United States. Shi Ying's co-authors include Baowen Xu, Xiao‐Yuan Jing, Xiaoke Zhu, Zhiqiang Li, Kun Zhu, Dandan Zhu, Hongyu Zhang, Fei Wu, Bryan Rink and Kirk Roberts and has published in prestigious journals such as Energy, Information Sciences and IEEE Transactions on Software Engineering.

In The Last Decade

Shi Ying

29 papers receiving 463 citations

Peers

Shi Ying
Yuchen Guo China
Chao Ni China
Alireza Khalilian Iran
Jun Ai China
Passakorn Phannachitta Japan
Daniel Weise United States
Detlef Streitferdt Germany
Uwe Ryssel Germany
Tian Jiang China
Yichen Zhu China
Yuchen Guo China
Shi Ying
Citations per year, relative to Shi Ying Shi Ying (= 1×) peers Yuchen Guo

Countries citing papers authored by Shi Ying

Since Specialization
Citations

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

Fields of papers citing papers by Shi Ying

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shi Ying

This figure shows the co-authorship network connecting the top 25 collaborators of Shi Ying. A scholar is included among the top collaborators of Shi Ying 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 Shi Ying. Shi Ying 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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Ying, Shi, et al.. (2022). Underestimation estimators to Q-learning. Information Sciences. 607. 173–185. 8 indexed citations
5.
Zhu, Kun, et al.. (2021). Software defect prediction based on enhanced metaheuristic feature selection optimization and a hybrid deep neural network. Journal of Systems and Software. 180. 111026–111026. 73 indexed citations
6.
Ying, Shi, et al.. (2021). Software defect prediction based on stacked sparse denoising autoencoders and enhanced extreme learning machine. IET Software. 16(1). 29–47. 14 indexed citations
7.
Zhu, Kun, Shi Ying, Weiping Ding, Nana Zhang, & Dandan Zhu. (2021). IVKMP: A robust data-driven heterogeneous defect model based on deep representation optimization learning. Information Sciences. 583. 332–363. 11 indexed citations
8.
Zhu, Kun, et al.. (2020). Software Defect Prediction Based on Stacked Contractive Autoencoder and Multi-objective Optimization. Computers, materials & continua/Computers, materials & continua (Print). 65(1). 279–308. 8 indexed citations
9.
Li, Zhiqiang, Xiao‐Yuan Jing, Xiaoke Zhu, et al.. (2019). Heterogeneous defect prediction with two-stage ensemble learning. Automated Software Engineering. 26(3). 599–651. 51 indexed citations
10.
Ying, Shi, et al.. (2017). Automated Change Diagnosis of Single-Column-Pier Bridges Based on 3D Imagery Data. 91–98. 3 indexed citations
11.
Li, Zhiqiang, Xiao‐Yuan Jing, Fei Wu, et al.. (2017). Cost-sensitive transfer kernel canonical correlation analysis for heterogeneous defect prediction. Automated Software Engineering. 25(2). 201–245. 96 indexed citations
12.
Li, Zhiqiang, Xiao‐Yuan Jing, Xiaoke Zhu, et al.. (2017). On the Multiple Sources and Privacy Preservation Issues for Heterogeneous Defect Prediction. IEEE Transactions on Software Engineering. 45(4). 391–411. 87 indexed citations
13.
Jing, Wen, et al.. (2011). Toward a Software Architectural Design Approach for Trusted Software Based on Monitoring. Chinese Journal of Computers. 33(12). 2321–2334. 3 indexed citations
14.
Ying, Shi, et al.. (2011). An aspect-oriented software architectural design method based on AC2-ADL. 1506–1513. 1 indexed citations
15.
Ying, Shi, et al.. (2010). Speech emotion recognition based on data mining technology. 2010 Sixth International Conference on Natural Computation. 17. 615–619. 9 indexed citations
16.
Ying, Shi, et al.. (2009). Modeling Aspect-Oriented Software Architecture. 4089. 108–113. 1 indexed citations
17.
Zhang, Lin‐Lin, et al.. (2008). A Generic Model for Multi-Dimensional Separation of Concerns at Architecture Level. 2830. 1–4. 1 indexed citations
18.
Ming, Zhong, et al.. (2006). An approach to manage and search for software components. 358–363.
19.
Hickl, Andrew, et al.. (2006). Question Answering with LCC's CHAUCER-2 at TREC 2007. Text REtrieval Conference. 33 indexed citations
20.
Ying, Shi, et al.. (2000). Specifying requirements of real-time system with rules and templates. Wuhan University Journal of Natural Sciences. 5(3). 278–284. 2 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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