Xiangyu Chang

141 total papers · 2.3k total citations
68 papers, 1.5k citations indexed

About

Xiangyu Chang is a scholar working on Artificial Intelligence, Computational Mechanics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Xiangyu Chang has authored 68 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 16 papers in Computational Mechanics and 13 papers in Computer Vision and Pattern Recognition. Recurrent topics in Xiangyu Chang's work include Sparse and Compressive Sensing Techniques (14 papers), Complex Network Analysis Techniques (10 papers) and Advanced Clustering Algorithms Research (6 papers). Xiangyu Chang is often cited by papers focused on Sparse and Compressive Sensing Techniques (14 papers), Complex Network Analysis Techniques (10 papers) and Advanced Clustering Algorithms Research (6 papers). Xiangyu Chang collaborates with scholars based in China, United States and Hong Kong. Xiangyu Chang's co-authors include Yao Wang, Zongben Xu, Yong Liang, Hai Zhang, Xin Bo, Shouyang Wang, Ling Tang, Zhifu Mi, Xiaoda Xue and Shibei Li and has published in prestigious journals such as PLoS ONE, Scientific Reports and IEEE Transactions on Signal Processing.

In The Last Decade

Xiangyu Chang

60 papers receiving 1.5k citations

Hit Papers

Substantial emission redu... 2010 2026 2015 2020 2019 2010 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Xiangyu Chang 312 290 255 255 210 68 1.5k
Zhaoyuan Yu 192 0.6× 328 1.1× 118 0.5× 54 0.2× 121 0.6× 130 1.8k
Valeria V. Krzhizhanovskaya 416 1.3× 122 0.4× 58 0.2× 181 0.7× 65 0.3× 116 2.1k
Rossella Arcucci 266 0.9× 84 0.3× 84 0.3× 197 0.8× 437 2.1× 87 1.5k
Nikos Deligiannis 218 0.7× 550 1.9× 183 0.7× 288 1.1× 50 0.2× 150 1.6k
Wenjian Wang 781 2.5× 457 1.6× 299 1.2× 48 0.2× 138 0.7× 107 2.2k
Jiawei Tian 477 1.5× 176 0.6× 210 0.8× 27 0.1× 93 0.4× 63 1.9k
Linwang Yuan 175 0.6× 316 1.1× 123 0.5× 47 0.2× 170 0.8× 94 1.5k
Wenyuan Liao 69 0.2× 56 0.2× 125 0.5× 276 1.1× 134 0.6× 94 1.4k
Bin Chen 239 0.8× 80 0.3× 128 0.5× 67 0.3× 52 0.2× 168 1.8k
Xiaohui Huang 509 1.6× 420 1.4× 39 0.2× 41 0.2× 291 1.4× 104 1.9k

Countries citing papers authored by Xiangyu Chang

Since Specialization
Citations

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

Fields of papers citing papers by Xiangyu Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiangyu Chang

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

All Works

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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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