Ilsoon Yang

2.4k total citations · 1 hit paper
10 papers, 1.7k citations indexed

About

Ilsoon Yang is a scholar working on Statistics and Probability, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Ilsoon Yang has authored 10 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Statistics and Probability, 2 papers in Artificial Intelligence and 2 papers in Computational Theory and Mathematics. Recurrent topics in Ilsoon Yang's work include Statistical Methods and Bayesian Inference (5 papers), Statistical Methods and Inference (4 papers) and Advanced Multi-Objective Optimization Algorithms (2 papers). Ilsoon Yang is often cited by papers focused on Statistical Methods and Bayesian Inference (5 papers), Statistical Methods and Inference (4 papers) and Advanced Multi-Objective Optimization Algorithms (2 papers). Ilsoon Yang collaborates with scholars based in United States. Ilsoon Yang's co-authors include Kenneth Lange, David R. Hunter, Z. Ying, D. Y. Lin, L. J. Wei, Mark P. Becker, Janice K. Albrecht, John G. McHutchison, Stephen Pianko and John E. Ware and has published in prestigious journals such as Biometrics, Journal of Hepatology and Journal of the Royal Statistical Society Series B (Statistical Methodology).

In The Last Decade

Ilsoon Yang

10 papers receiving 1.7k citations

Hit Papers

Semiparametric Regression for the Mean and Rate Functions... 2000 2026 2008 2017 2000 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ilsoon Yang United States 8 683 305 225 208 190 10 1.7k
Shinto Eguchi Japan 26 734 1.1× 533 1.7× 76 0.3× 76 0.4× 218 1.1× 108 1.9k
Anru R. Zhang United States 22 296 0.4× 235 0.8× 548 2.4× 136 0.7× 163 0.9× 67 1.5k
Yuedong Wang United States 30 459 0.7× 153 0.5× 39 0.2× 126 0.6× 58 0.3× 112 2.6k
Hung Hung United States 28 1.5k 2.2× 116 0.4× 130 0.6× 93 0.4× 24 0.1× 114 2.9k
David Madigan United States 24 427 0.6× 690 2.3× 40 0.2× 239 1.1× 180 0.9× 47 2.6k
Jiguo Cao Canada 24 419 0.6× 394 1.3× 32 0.1× 93 0.4× 98 0.5× 120 2.4k
Aleksandr Y. Aravkin United States 28 76 0.1× 296 1.0× 318 1.4× 154 0.7× 380 2.0× 118 3.0k
Berwin A. Turlach Australia 24 702 1.0× 430 1.4× 329 1.5× 85 0.4× 261 1.4× 84 2.2k
Craig B. Borkowf United States 25 153 0.2× 160 0.5× 23 0.1× 853 4.1× 94 0.5× 63 3.1k
Christopher Jennison United Kingdom 25 3.2k 4.7× 325 1.1× 91 0.4× 74 0.4× 240 1.3× 79 4.4k

Countries citing papers authored by Ilsoon Yang

Since Specialization
Citations

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

Fields of papers citing papers by Ilsoon Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ilsoon Yang

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

All Works

10 of 10 papers shown
1.
McHutchison, John G., John E. Ware, Martha Bayliss, et al.. (2001). The effects of interferon alpha-2b in combination with ribavirin on health related quality of life and work productivity. Journal of Hepatology. 34(1). 140–147. 182 indexed citations
2.
Lange, Kenneth, David R. Hunter, & Ilsoon Yang. (2000). Optimization Transfer Using Surrogate Objective Functions. Journal of Computational and Graphical Statistics. 9(1). 1–20. 488 indexed citations
3.
Lin, D. Y., L. J. Wei, Ilsoon Yang, & Z. Ying. (2000). Semiparametric Regression for the Mean and Rate Functions of Recurrent Events. Journal of the Royal Statistical Society Series B (Statistical Methodology). 62(4). 711–730. 647 indexed citations breakdown →
4.
Lange, Kenneth, David R. Hunter, & Ilsoon Yang. (2000). Optimization Transfer Using Surrogate Objective Functions. Journal of Computational and Graphical Statistics. 9(1). 1–1. 213 indexed citations
5.
Becker, Mark P. & Ilsoon Yang. (1998). 7. Latent Class Marginal Models for Cross-Classifications of Counts. Sociological Methodology. 28(1). 293–325. 18 indexed citations
6.
Becker, Mark P., et al.. (1998). Specifications of Models for Cross-Classified Counts. Sociological Methods & Research. 26(4). 511–529. 4 indexed citations
7.
Becker, Mark P., Ilsoon Yang, & Kenneth Lange. (1997). EM algorithms without missing data. Statistical Methods in Medical Research. 6(1). 38–54. 55 indexed citations
8.
Yang, Ilsoon, et al.. (1997). EM algorithms without missing data. Statistical Methods in Medical Research. 6(1). 38–54. 18 indexed citations
9.
Yang, Ilsoon & Mark P. Becker. (1997). Latent Variable Modeling of Diagnostic Accuracy. Biometrics. 53(3). 948–948. 120 indexed citations
10.
Yang, Ilsoon. (1996). Latent class marginal models for the analysis of cross-classified categorical data.. Deep Blue (University of Michigan). 3 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.

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