Ruijin Cang

601 total citations
7 papers, 448 citations indexed

About

Ruijin Cang is a scholar working on Materials Chemistry, Civil and Structural Engineering and Artificial Intelligence. According to data from OpenAlex, Ruijin Cang has authored 7 papers receiving a total of 448 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Materials Chemistry, 3 papers in Civil and Structural Engineering and 3 papers in Artificial Intelligence. Recurrent topics in Ruijin Cang's work include Machine Learning in Materials Science (4 papers), Topology Optimization in Engineering (3 papers) and Injection Molding Process and Properties (3 papers). Ruijin Cang is often cited by papers focused on Machine Learning in Materials Science (4 papers), Topology Optimization in Engineering (3 papers) and Injection Molding Process and Properties (3 papers). Ruijin Cang collaborates with scholars based in United States. Ruijin Cang's co-authors include Yang Jiao, Yi Ren, Houpu Yao, Yongming Liu, Shaohua Chen, Danny J. Lohan and James T. Allison and has published in prestigious journals such as Computational Materials Science, Journal of Mechanical Design and Computer-Aided Design.

In The Last Decade

Ruijin Cang

7 papers receiving 437 citations

Peers

Ruijin Cang
Houpu Yao United States
Ruijin Cang
Citations per year, relative to Ruijin Cang Ruijin Cang (= 1×) peers Houpu Yao

Countries citing papers authored by Ruijin Cang

Since Specialization
Citations

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

Fields of papers citing papers by Ruijin Cang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruijin Cang

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

All Works

7 of 7 papers shown
1.
Cang, Ruijin, Houpu Yao, & Yi Ren. (2019). One-shot generation of near-optimal topology through theory-driven machine learning. Computer-Aided Design. 109. 12–21. 55 indexed citations
3.
Lohan, Danny J., et al.. (2018). An Indirect Design Representation for Topology Optimization Using Variational Autoencoder and Style Transfer. 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. 61 indexed citations
4.
Cang, Ruijin, Houpu Yao, & Yi Ren. (2018). One-Shot Optimal Topology Generation through Theory-Driven Machine Learning.. 1 indexed citations
5.
Cang, Ruijin, et al.. (2017). Scalable Microstructure Reconstruction With Multi-Scale Pattern Preservation. 4 indexed citations
6.
Cang, Ruijin, et al.. (2017). Microstructure Representation and Reconstruction of Heterogeneous Materials Via Deep Belief Network for Computational Material Design. Journal of Mechanical Design. 139(7). 145 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026