Johan Lim

2.3k total citations
143 papers, 1.6k citations indexed

About

Johan Lim is a scholar working on Statistics and Probability, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Johan Lim has authored 143 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Statistics and Probability, 44 papers in Molecular Biology and 28 papers in Artificial Intelligence. Recurrent topics in Johan Lim's work include Statistical Methods and Inference (35 papers), Statistical Methods and Bayesian Inference (25 papers) and Advanced Statistical Methods and Models (24 papers). Johan Lim is often cited by papers focused on Statistical Methods and Inference (35 papers), Statistical Methods and Bayesian Inference (25 papers) and Advanced Statistical Methods and Models (24 papers). Johan Lim collaborates with scholars based in South Korea, United States and Vietnam. Johan Lim's co-authors include Sung Won Kwon, Xinlei Wang, Jeong Hill Park, Donghyeon Yu, Jeongmi Lee, Lynne Stokes, Joong‐Ho Won, Bala Rajaratnam, Soohyun Ahn and Guanghua Xiao and has published in prestigious journals such as Journal of the American Statistical Association, PLoS ONE and Scientific Reports.

In The Last Decade

Johan Lim

124 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Johan Lim South Korea 23 505 404 157 148 148 143 1.6k
Ricardo Cao Spain 29 394 0.8× 897 2.2× 162 1.0× 429 2.9× 128 0.9× 164 2.6k
Naisyin Wang United States 27 641 1.3× 644 1.6× 115 0.7× 240 1.6× 38 0.3× 63 2.2k
Olle Nerman Sweden 25 863 1.7× 249 0.6× 145 0.9× 136 0.9× 52 0.4× 58 2.9k
Eugene F. Schuster United States 28 1.6k 3.2× 523 1.3× 118 0.8× 252 1.7× 83 0.6× 84 4.2k
Paolo Magni Italy 27 986 2.0× 163 0.4× 40 0.3× 200 1.4× 40 0.3× 136 2.4k
Hani Doss United States 19 292 0.6× 515 1.3× 34 0.2× 401 2.7× 60 0.4× 45 1.7k
Yang Feng United States 26 655 1.3× 846 2.1× 31 0.2× 630 4.3× 65 0.4× 115 2.7k
E. Olusegun George United States 15 196 0.4× 223 0.6× 97 0.6× 118 0.8× 43 0.3× 54 749
Hyonho Chun United States 13 462 0.9× 146 0.4× 53 0.3× 73 0.5× 20 0.1× 24 1.1k
Jie Peng China 24 964 1.9× 325 0.8× 508 3.2× 192 1.3× 9 0.1× 115 2.6k

Countries citing papers authored by Johan Lim

Since Specialization
Citations

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

Fields of papers citing papers by Johan Lim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Johan Lim

This figure shows the co-authorship network connecting the top 25 collaborators of Johan Lim. A scholar is included among the top collaborators of Johan Lim 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 Johan Lim. Johan Lim 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
1.
Lim, Johan, Seung‐Kyu Kim, & Donghyeon Yu. (2025). A comprehensive and empirical review of the synthpop for synthetic data generation. Korean Journal of Applied Statistics. 38(2). 299–308.
2.
Park, Seongoh, Joungyoun Kim, Xinlei Wang, & Johan Lim. (2024). Variable selection in Bayesian multiple instance regression using shotgun stochastic search. Computational Statistics & Data Analysis. 196. 107954–107954.
3.
Kim, Joungyoun, et al.. (2023). Post Hotelling's T -square procedure to identify fault variables. Journal of Statistical Computation and Simulation. 94(1). 1–28. 2 indexed citations
4.
Park, Seongoh & Johan Lim. (2022). An overview of heavy-tail extensions of multivariate Gaussian distribution and their relations. Journal of Applied Statistics. 49(13). 3477–3494.
5.
Koh, Jung Hee, Sang Jun Yoon, Mi‐Na Kim, et al.. (2022). Lipidome profile predictive of disease evolution and activity in rheumatoid arthritis. Experimental & Molecular Medicine. 54(2). 143–155. 37 indexed citations
6.
Park, Seongoh, Xinlei Wang, Johan Lim, et al.. (2020). Bayesian multiple instance regression for modeling immunogenic neoantigens. Statistical Methods in Medical Research. 29(10). 3032–3047. 6 indexed citations
7.
Yu, Donghyeon, Sang H. Lee, Johan Lim, et al.. (2018). Fused lasso regression for identifying differential correlations in brain connectome graphs. Statistical Analysis and Data Mining The ASA Data Science Journal. 11(5). 203–226. 3 indexed citations
8.
Lee, Taehoon, Joong‐Ho Won, Johan Lim, & Sungroh Yoon. (2017). Large-Scale Structured Sparsity via Parallel Fused Lasso on Multiple GPUs. Journal of Computational and Graphical Statistics. 26(4). 851–864. 3 indexed citations
9.
Yu, Donghyeon, Johan Lim, Xinlei Wang, Faming Liang, & Guanghua Xiao. (2017). Enhanced construction of gene regulatory networks using hub gene information. BMC Bioinformatics. 18(1). 186–186. 94 indexed citations
10.
Lim, Dong Kyu, et al.. (2015). Expeditious discrimination of four species of the Panax genus using direct infusion-MS/MS combined with multivariate statistical analysis. Journal of Chromatography B. 1002. 329–336. 23 indexed citations
11.
Lee, Sang H., Donghyeon Yu, Alvin H. Bachman, Johan Lim, & Babak A. Ardekani. (2013). Application of fused lasso logistic regression to the study of corpus callosum thickness in early Alzheimer's disease. Journal of Neuroscience Methods. 221. 78–84. 23 indexed citations
12.
Lim, Johan, et al.. (2012). Detection of Differentially Expressed Gene Sets in a Partially Paired Microarray Data Set. Statistical Applications in Genetics and Molecular Biology. 11(3). Article 5–Article 5. 3 indexed citations
13.
Lee, Sang H., et al.. (2012). Input permutation method to detect active voxels in fMRI study. Magnetic Resonance Imaging. 30(10). 1495–1504. 3 indexed citations
14.
Sohn, Insuk, et al.. (2011). Multiple testing for gene sets from microarray experiments. BMC Bioinformatics. 12(1). 209–209. 5 indexed citations
15.
Wang, Xinlei, Ke Wang, & Johan Lim. (2011). Isotonized CDF Estimation from Judgment Poststratification Data with Empty Strata. Biometrics. 68(1). 194–202. 28 indexed citations
16.
Chai, Chuan, Hyun Kyoung Ju, Sang Cheol Kim, et al.. (2011). Determination of bioactive compounds in fermented soybean products using GC/MS and further investigation of correlation of their bioactivities. Journal of Chromatography B. 880(1). 42–49. 46 indexed citations
17.
18.
Wang, Xinlei, Johan Lim, & Lynne Stokes. (2008). A Nonparametric Mean Estimator for Judgment Poststratified Data. Biometrics. 64(2). 355–363. 42 indexed citations
19.
Lim, Johan, et al.. (2007). Image Segmentation Using Hidden Markov Gauss Mixture Models. IEEE Transactions on Image Processing. 16(7). 1902–1911. 35 indexed citations
20.
Lee, Shin‐Jae, et al.. (2007). Cluster analysis of tooth size in subjects with normal occlusion. American Journal of Orthodontics and Dentofacial Orthopedics. 132(6). 796–800. 20 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Ricardo Cao Breakdown of academic impact, for papers by Naisyin Wang Breakdown of academic impact, for papers by Olle Nerman Breakdown of academic impact, for papers by Eugene F. Schuster Breakdown of academic impact, for papers by Paolo Magni Breakdown of academic impact, for papers by Hani Doss Breakdown of academic impact, for papers by Yang Feng Breakdown of academic impact, for papers by E. Olusegun George Breakdown of academic impact, for papers by Hyonho Chun Breakdown of academic impact, for papers by Jie Peng
Rankless by CCL
2026