Shiyu Chang

270 total papers · 9.4k total citations
108 papers, 3.8k citations indexed

About

Shiyu Chang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Shiyu Chang has authored 108 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Artificial Intelligence, 61 papers in Computer Vision and Pattern Recognition and 12 papers in Signal Processing. Recurrent topics in Shiyu Chang's work include Topic Modeling (17 papers), Domain Adaptation and Few-Shot Learning (14 papers) and Natural Language Processing Techniques (14 papers). Shiyu Chang is often cited by papers focused on Topic Modeling (17 papers), Domain Adaptation and Few-Shot Learning (14 papers) and Natural Language Processing Techniques (14 papers). Shiyu Chang collaborates with scholars based in United States, China and Singapore. Shiyu Chang's co-authors include Thomas S. Huang, Shuicheng Yan, Ding Liu, Mo Yu, Zhangyang Wang, Wei Han, Guo-Jun Qi, Charų C. Aggarwal, Yifan Jiang and Jiliang Tang and has published in prestigious journals such as IEEE Transactions on Image Processing, eLife and Frontiers in Oncology.

In The Last Decade

Shiyu Chang

102 papers receiving 3.6k citations

Hit Papers

Heterogeneous Network Emb... 2013 2026 2017 2021 2015 2013 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
Shiyu Chang 2.2k 1.9k 365 359 300 108 3.8k
Liangliang Cao 2.8k 1.3× 1.5k 0.8× 245 0.7× 378 1.1× 430 1.4× 110 4.1k
Sebastian Nowozin 2.7k 1.3× 1.7k 0.9× 437 1.2× 289 0.8× 259 0.9× 77 4.4k
Liefeng Bo 3.9k 1.8× 1.8k 1.0× 470 1.3× 376 1.0× 269 0.9× 79 5.9k
Zhongfei Zhang 3.6k 1.7× 2.3k 1.2× 342 0.9× 217 0.6× 430 1.4× 210 5.5k
Dong Huang 2.6k 1.2× 2.2k 1.2× 440 1.2× 142 0.4× 272 0.9× 173 4.5k
Quanming Yao 1.5k 0.7× 2.4k 1.3× 424 1.2× 183 0.5× 262 0.9× 89 4.2k
Zhao Kang 2.8k 1.3× 2.3k 1.2× 760 2.1× 121 0.3× 237 0.8× 95 4.1k
Ji‐Xiang Du 1.3k 0.6× 1.1k 0.6× 246 0.7× 145 0.4× 389 1.3× 123 3.1k
Wei Peng 1.4k 0.7× 1.3k 0.7× 123 0.3× 457 1.3× 333 1.1× 120 3.2k
Jiancheng Lv 2.0k 0.9× 1.8k 1.0× 330 0.9× 171 0.5× 137 0.5× 194 3.8k

Countries citing papers authored by Shiyu Chang

Since Specialization
Citations

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

Fields of papers citing papers by Shiyu Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shiyu Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Shiyu Chang. A scholar is included among the top collaborators of Shiyu 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 Shiyu Chang. Shiyu 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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