Jooyong Shim

583 citations
63 papers · 382 indexed · h-index 10
Topics
Statistical Methods and Inference (22 papers)Face and Expression Recognition (18 papers)Advanced Statistical Methods and Models (17 papers)
Partner nations
South KoreaUnited States

In The Last Decade

Jooyong Shim

56 papers receiving 340 citations

Peers

Jooyong Shim
Comparison fields: 5 of 94
  • Statistics and Probability 113
  • Molecular Biology 85
  • Artificial Intelligence 77
  • Control and Systems Engineering 62
  • Computational Theory and Mathematics 57
Replace Xin Dang with:
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Citations per field
00.5×2.6×
Xin Dang · 1×
Citations per year

Countries citing papers authored by Jooyong Shim

Since Specialization
Citations

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

Fields of papers citing papers by Jooyong Shim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jooyong Shim

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 57
3 1
4 18
5 11
6
Variable selection in L1 penalized censored regression
1
7
Cox proportional hazard model with L1 penalty
1
8
Variable selection in the kernel Cox regression
1
9
Estimation of nonlinear GARCH-M model
1
10
Restricted support vector quantile regression without crossing
4
11
Doubly penalized kernel method for heteroscedastic autoregressive datay
5
12
Semiparametric support vector machine for accelerated failure time model
4
13
A kernel machine for estimation of mean and volatility functions
1
14
Credibility estimation via kernel mixed effects model
0
15
Kernel method for autoregressive data
8
16
Kernel Poisson Regression for Longitudinal Data
7
17
Claims Reserving via Kernel Machine
4
18
Censored Kernel Ridge Regression
4
19
e-SVR using IRWLS Procedure
1
20
Prediction Intervals for LS-SVM Regression using the Bootstrap
4

About Jooyong Shim

Jooyong Shim is a scholar working on Statistics and Probability, Computer Vision and Pattern Recognition and Analytical Chemistry, having authored 63 papers that have together received 382 indexed citations. Recurring topics across this work include Statistical Methods and Inference (22 papers), Face and Expression Recognition (18 papers) and Advanced Statistical Methods and Models (17 papers). The work is most often cited by research in Statistics and Probability (113 citations), Management Science and Operations Research (54 citations) and Computational Theory and Mathematics (57 citations). Jooyong Shim has collaborated with scholars based in South Korea and United States. Frequent co-authors include Changha Hwang, Insuk Sohn, Yongtae Kim, Youngmin Kim, Sujong Kim, Woo‐Chan Son, Jae Won Lee, Sangwoo Seo, Paul E. Green and Gyu‐Jeong Noh. Their work appears in journals such as PLoS ONE, Scientific Reports and Neurocomputing.

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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