Wei-Chien Chang

17 total papers · 477 total citations
12 papers, 321 citations indexed

About

Wei-Chien Chang is a scholar working on Artificial Intelligence, Statistics and Probability and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Wei-Chien Chang has authored 12 papers receiving a total of 321 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 6 papers in Statistics and Probability and 2 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Wei-Chien Chang's work include Advanced Statistical Methods and Models (6 papers), Bayesian Methods and Mixture Models (5 papers) and Market Dynamics and Volatility (2 papers). Wei-Chien Chang is often cited by papers focused on Advanced Statistical Methods and Models (6 papers), Bayesian Methods and Mixture Models (5 papers) and Market Dynamics and Volatility (2 papers). Wei-Chien Chang collaborates with scholars based in United States, Taiwan and Canada. Wei-Chien Chang's co-authors include Wei Tan, Jia‐Yush Yen, Chih‐Kung Lee and Ming‐Wei Chang and has published in prestigious journals such as Journal of the American Statistical Association, Technometrics and Biometrics.

In The Last Decade

Wei-Chien Chang

12 papers receiving 276 citations

Author Peers

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

Author Last Decade Papers Cites
Wei-Chien Chang 160 98 59 42 31 12 321
Louis Ferré 62 0.4× 155 1.6× 35 0.6× 24 0.6× 35 1.1× 16 318
Otto Opitz 98 0.6× 34 0.3× 41 0.7× 28 0.7× 18 0.6× 18 314
Michael Tso 56 0.3× 82 0.8× 31 0.5× 52 1.2× 44 1.4× 11 361
John Van Ness 80 0.5× 117 1.2× 61 1.0× 32 0.8× 36 1.2× 11 301
Adrian Corduneanu 231 1.4× 43 0.4× 62 1.1× 31 0.7× 11 0.4× 10 324
Wendy L. Poston 135 0.8× 122 1.2× 48 0.8× 21 0.5× 6 0.2× 17 342
Michael J. Prentice 75 0.5× 75 0.8× 29 0.5× 76 1.8× 3 0.1× 16 339
Rüdiger Klar 80 0.5× 12 0.1× 31 0.5× 55 1.3× 10 0.3× 17 238
Ci‐Ren Jiang 55 0.3× 124 1.3× 14 0.2× 99 2.4× 22 0.7× 14 317
Sania Anam 75 0.5× 37 0.4× 36 0.6× 12 0.3× 44 1.4× 19 329

Countries citing papers authored by Wei-Chien Chang

Since Specialization
Citations

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

Fields of papers citing papers by Wei-Chien Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wei-Chien Chang

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