Il Do Ha

1.1k total citations
61 papers, 827 citations indexed

About

Il Do Ha is a scholar working on Statistics and Probability, Demography and Economics and Econometrics. According to data from OpenAlex, Il Do Ha has authored 61 papers receiving a total of 827 indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Statistics and Probability, 19 papers in Demography and 12 papers in Economics and Econometrics. Recurrent topics in Il Do Ha's work include Statistical Methods and Inference (42 papers), Statistical Methods and Bayesian Inference (29 papers) and Insurance, Mortality, Demography, Risk Management (19 papers). Il Do Ha is often cited by papers focused on Statistical Methods and Inference (42 papers), Statistical Methods and Bayesian Inference (29 papers) and Insurance, Mortality, Demography, Risk Management (19 papers). Il Do Ha collaborates with scholars based in South Korea, United States and Ireland. Il Do Ha's co-authors include Youngjo Lee, Jong‐Hyeon Jeong, Gilbert MacKenzie, Chi‐Heum Cho, Young Kyu Kwon, So‐Jin Shin, Dae Hyun Kim, Mi Kyung Kim, Young Sung Suh and Jae Seok Hwang and has published in prestigious journals such as Biometrika, IEEE Access and Statistics in Medicine.

In The Last Decade

Il Do Ha

49 papers receiving 786 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Il Do Ha South Korea	16	436	132	110	87	73	61	827
Driss Oraichi Canada	14	247 0.6×	7 0.1×	100 0.9×	75 0.9×	72 1.0×	26	1.2k
Grace Y. Yi Canada	18	673 1.5×	13 0.1×	122 1.1×	163 1.9×	34 0.5×	66	883
Joseph L. Ciminera United States	9	225 0.5×	18 0.1×	29 0.3×	17 0.2×	86 1.2×	22	674
B. W. Turnbull United States	11	103 0.2×	5 0.0×	22 0.2×	24 0.3×	102 1.4×	20	826
Yifan Cui China	11	165 0.4×	4 0.0×	49 0.4×	32 0.4×	82 1.1×	34	458
Keewhan Choi United States	16	140 0.3×	13 0.1×	11 0.1×	69 0.8×	143 2.0×	22	994
Rehan Ahmad Khan Sherwani Pakistan	10	128 0.3×	5 0.0×	17 0.2×	27 0.3×	15 0.2×	45	349
Hongshik Ahn United States	14	161 0.4×	4 0.0×	17 0.2×	46 0.5×	50 0.7×	51	580
J. Burridge United Kingdom	11	135 0.3×	4 0.0×	25 0.2×	74 0.9×	13 0.2×	18	440
María Eugenia Castellanos Spain	13	129 0.3×	3 0.0×	13 0.1×	43 0.5×	72 1.0×	45	508

Countries citing papers authored by Il Do Ha

Since Specialization

Citations

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

Fields of papers citing papers by Il Do Ha

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Il Do Ha. 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 Il Do Ha. The network helps show where Il Do Ha may publish in the future.

Co-authorship network of co-authors of Il Do Ha

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

All Works

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20 of 20 papers shown

Ha, Il Do, et al.. (2025). CNN-Based Approaches for Various Types of Tabular Data. IEEE Access. 13. 200537–200554.

Ha, Il Do, et al.. (2025). Vine copula MFPCA residual control chart for sparse multivariate functional data. Communications in Statistics - Simulation and Computation. 54(12). 5369–5389. 1 indexed citations

Kim, Jong‐Min, Il Do Ha, & Sang-Jin Kim. (2025). Deep learning-based survival analysis with copula-based activation functions for multivariate response prediction. Computational Statistics. 40(9). 5649–5676.

Ha, Il Do, et al.. (2024). Semiparametric accelerated failure time models under unspecified random effect distributions. Computational Statistics & Data Analysis. 195. 107958–107958.

Ha, Il Do, et al.. (2024). Likelihood-Based Inference of Log-Logistic Accelerated Hazards Regression Models for Cross Hazards Data. Measurement Interdisciplinary Research and Perspectives. 24(1). 66–84.

Ha, Il Do & Kevin Burke. (2024). Fitting deep neural networks into the statistical regression modelling setting. Japanese Journal of Statistics and Data Science. 8(1). 425–449.

Lin, Hao, Il Do Ha, Jong‐Hyeon Jeong, & Youngjo Lee. (2024). Joint AFT random-effect modeling approach for clustered competing-risks data. Journal of Statistical Computation and Simulation. 94(10). 2114–2142.

Ha, Il Do, et al.. (2023). Penalized variable selection in multi-parameter regression survival modeling. Statistical Methods in Medical Research. 32(12). 2455–2471.

Kim, Jong‐Min & Il Do Ha. (2022). Deep learning-based residual control chart for count data. Quality Engineering. 34(3). 370–381. 13 indexed citations

10.

Kim, Jong‐Min, et al.. (2022). Application of Deep Learning and Neural Network to Speeding Ticket and Insurance Claim Count Data. Axioms. 11(6). 280–280. 2 indexed citations

11.

Ha, Il Do, et al.. (2019). Frailty modelling approaches for semi-competing risks data. Lifetime Data Analysis. 26(1). 109–133. 10 indexed citations

12.

Emura, Takeshi, et al.. (2019). Comparison of the marginal hazard model and the sub-distribution hazard model for competing risks under an assumed copula. Statistical Methods in Medical Research. 29(8). 2307–2327. 28 indexed citations

13.

Lim, Jae‐Sung, Beom Joon Kim, Moon‐Ku Han, et al.. (2017). A Methodological Perspective on the Longitudinal Cognitive Change after Stroke. Dementia and Geriatric Cognitive Disorders. 44(5-6). 311–319. 7 indexed citations

14.

Ha, Il Do. (2016). ML estimation using Poisson HGLM approach in semi-parametric frailty models. Journal of the Korean Data and Information Science Society. 27(5). 1389–1397. 1 indexed citations

15.

Ha, Il Do, Richard Sylvester, Catherine Legrand, & Gilbert MacKenzie. (2011). Frailty modelling for survival data from multi‐centre clinical trials. Statistics in Medicine. 30(17). 2144–2159. 37 indexed citations

16.

Ha, Il Do, et al.. (2009). Survey of Oriental Medical Care for Traffic Accident Patients with Automobile insurance; 544 Cases Report. Journal of Acupuncture Research. 26(3). 1–10. 20 indexed citations

17.

Ha, Il Do, Youngjo Lee, & Yudi Pawitan. (2007). Genetic Mixed Linear Models for Twin Survival Data. Behavior Genetics. 37(4). 621–630. 6 indexed citations

18.

Ha, Il Do, Youngjo Lee, & Gilbert MacKenzie. (2007). Model selection for multi‐component frailty models. Statistics in Medicine. 26(26). 4790–4807. 32 indexed citations

19.

Ha, Il Do & Youngjo Lee. (2005). Multilevel Mixed Linear Models for Survival Data. Lifetime Data Analysis. 11(1). 131–142. 27 indexed citations

20.

Ha, Il Do, et al.. (2002). Hierarchical-Likelihood Approach for Mixed Linear Models with Censored Data. Lifetime Data Analysis. 8(2). 163–176. 34 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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