Liang Yan

63 papers and 1.3k indexed citations i.

About

Liang Yan is a scholar working on Mathematical Physics, Statistics, Probability and Uncertainty and Artificial Intelligence. According to data from OpenAlex, Liang Yan has authored 63 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Mathematical Physics, 15 papers in Statistics, Probability and Uncertainty and 14 papers in Artificial Intelligence. Recurrent topics in Liang Yan’s work include Inverse Problems in Mathematical Physics and Imaging (18 papers), Probabilistic and Robust Engineering Design (15 papers) and Model Reduction and Neural Networks (10 papers). Liang Yan is often cited by papers focused on Inverse Problems in Mathematical Physics and Imaging (18 papers), Probabilistic and Robust Engineering Design (15 papers) and Model Reduction and Neural Networks (10 papers). Liang Yan collaborates with scholars based in China, United States and Japan. Liang Yan's co-authors include Fenglian Yang, Chu‐Li Fu, Tao Tang, Ling Guo, Lawrence J. Singerman, Mark S. Rzeszotarski, Dongbin Xiu, Biao Yan, Zhiwei Gao and Masahiro Yamamoto and has published in prestigious journals such as Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering and IEEE Transactions on Medical Imaging.

In The Last Decade

Co-authorship network of co-authors of Liang Yan i

Fields of papers citing papers by Liang Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Liang Yan

Since Specialization
Citations

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

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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2025