Seung‐Ho Kang

889 total citations
63 papers, 627 citations indexed

About

Seung‐Ho Kang is a scholar working on Statistics and Probability, Ecology, Evolution, Behavior and Systematics and Plant Science. According to data from OpenAlex, Seung‐Ho Kang has authored 63 papers receiving a total of 627 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Statistics and Probability, 10 papers in Ecology, Evolution, Behavior and Systematics and 8 papers in Plant Science. Recurrent topics in Seung‐Ho Kang's work include Statistical Methods in Clinical Trials (12 papers), Statistical Methods and Bayesian Inference (8 papers) and Plant and animal studies (7 papers). Seung‐Ho Kang is often cited by papers focused on Statistical Methods in Clinical Trials (12 papers), Statistical Methods and Bayesian Inference (8 papers) and Plant and animal studies (7 papers). Seung‐Ho Kang collaborates with scholars based in South Korea, United States and Malaysia. Seung‐Ho Kang's co-authors include Sang‐Hee Lee, Kuinam J. Kim, Chul Ahn, Jung‐Hee Cho, James J. Chen, Sin‐Ho Jung, Dong Wan Shin, Suhee Song, Shein‐Chung Chow and Wonju Jeon and has published in prestigious journals such as Biometrics, Biochemical and Biophysical Research Communications and Journal of Econometrics.

In The Last Decade

Seung‐Ho Kang

56 papers receiving 598 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seung‐Ho Kang South Korea 15 120 108 106 79 75 63 627
Dayanand N. Naik United States 14 217 1.8× 26 0.2× 84 0.8× 48 0.6× 52 0.7× 40 875
Gerard Austin United Kingdom 2 94 0.8× 17 0.2× 41 0.4× 43 0.5× 37 0.5× 5 431
Wolfgang Trutschnig Austria 18 332 2.8× 13 0.1× 176 1.7× 58 0.7× 32 0.4× 83 1.0k
Rui Wu United States 11 49 0.4× 17 0.2× 58 0.5× 17 0.2× 64 0.9× 63 530
Juho Piironen Finland 6 158 1.3× 9 0.1× 126 1.2× 16 0.2× 56 0.7× 9 543
Mayer Alvo Canada 15 244 2.0× 74 0.7× 102 1.0× 21 0.3× 16 0.2× 57 662
Nathalie Peyrard France 12 43 0.4× 9 0.1× 177 1.7× 40 0.5× 21 0.3× 31 605
David Birkes United States 13 214 1.8× 8 0.1× 58 0.5× 188 2.4× 240 3.2× 32 761
David Smith Australia 5 49 0.4× 17 0.2× 36 0.3× 28 0.4× 17 0.2× 8 323
Marco Reale New Zealand 13 66 0.6× 12 0.1× 112 1.1× 33 0.4× 15 0.2× 50 584

Countries citing papers authored by Seung‐Ho Kang

Since Specialization
Citations

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

Fields of papers citing papers by Seung‐Ho Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seung‐Ho Kang. 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 Seung‐Ho Kang. The network helps show where Seung‐Ho Kang may publish in the future.

Co-authorship network of co-authors of Seung‐Ho Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Seung‐Ho Kang. A scholar is included among the top collaborators of Seung‐Ho Kang 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 Seung‐Ho Kang. Seung‐Ho Kang 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.
Kang, Seung‐Ho, et al.. (2024). Deep Reinforcement Learning for Multi-Objective Real-Time Pump Operation in Rainwater Pumping Stations. Water. 16(23). 3398–3398. 5 indexed citations
2.
Kang, Seung‐Ho, et al.. (2024). Comparative efficacy of vericiguat to sacubitril/valsartan for patients with heart failure reduced ejection fraction: Systematic review and network meta-analysis. International Journal of Cardiology. 400. 131786–131786. 4 indexed citations
3.
Kang, Seung‐Ho, et al.. (2022). ACGCN: Graph Convolutional Networks for Activity Cliff Prediction between Matched Molecular Pairs. Journal of Chemical Information and Modeling. 62(10). 2341–2351. 19 indexed citations
4.
Kang, Seung‐Ho, et al.. (2022). Status of legally protected species and specially designated species in Korea. 13(2). 1–13. 1 indexed citations
5.
6.
Kang, Seung‐Ho, et al.. (2020). Analysis of Insect Diversity in National Park Nature Resource Survey. Korean Journal of Environment and Ecology. 34(2). 130–141.
7.
Kim, Young‐Jin, et al.. (2017). Community structure and distribution of ground beetles (Coleoptera: Carabidae) in Sobaeksan National Park, Korea. Journal of Ecology and Environment. 41(1). 5 indexed citations
8.
Kang, Seung‐Ho, et al.. (2017). A Faunistic Study of Insects and Arenaceous Insects variation by Oil Spill Accidents of Taeanhaean National Park. Korean Journal of Environment and Ecology. 31(6). 500–507. 1 indexed citations
9.
Kim, Jangsuk, Jaeyong Lee, Ji-Young Park, et al.. (2016). Radiocarbon Dating and Old Wood Effect: An Experiment and Archaeological Assessment. 92(92). 117–149. 4 indexed citations
10.
Kim, Hong‐Gee, et al.. (2016). A Feature Selection Approach Based on Simulated Annealing for Detecting Various Denial of Service Attacks. 2016(1). 1–18. 3 indexed citations
11.
Kang, Seung‐Ho & Kuinam J. Kim. (2016). A feature selection approach to find optimal feature subsets for the network intrusion detection system. Cluster Computing. 19(1). 325–333. 71 indexed citations
12.
Kang, Seung‐Ho, et al.. (2015). Using hidden Markov models to characterize termite traveling behavior in tunnels with different curvatures. Behavioural Processes. 111. 101–108. 15 indexed citations
13.
Kang, Seung‐Ho, et al.. (2015). Sample Size Calculations for the Development of Biosimilar Products Based on Binary Endpoints. Communications for Statistical Applications and Methods. 22(4). 389–399. 2 indexed citations
14.
Kang, Seung‐Ho, et al.. (2010). A Branch and Bound Algorithm to Find a Routing Tree Having Minimum Wiener Index in Sensor Networks with High Mobile Base Node. The Journal of Korean Institute of Communications and Information Sciences. 35. 466–473.
15.
Kang, Seung‐Ho & Yi Tsong. (2010). Strength of evidence of non‐inferiority trials—The adjustment of the type I error rate in non‐inferiority trials with the synthesis method. Statistics in Medicine. 29(14). 1477–1487. 7 indexed citations
16.
Kang, Seung‐Ho, et al.. (2010). HapAssembler: A web server for haplotype assembly from SNP fragments using genetic algorithm. Biochemical and Biophysical Research Communications. 397(2). 340–344. 6 indexed citations
17.
Kang, Seung‐Ho, et al.. (2007). An Efficient Two-Phase Algorithm to Find Gene-Specific Probes for Large Genomes. 205–210. 1 indexed citations
18.
Ahn, Chul, Sin‐Ho Jung, & Seung‐Ho Kang. (2002). Modified regression coefficient analysis for repeated binary measurements. Journal of Applied Statistics. 29(5). 703–710. 3 indexed citations
19.
Yang, Mihi, Naoki Kunugita, Kyoko Kitagawa, et al.. (2001). Individual Differences in Urinary Cotinine Levels in Japanese Smokers. Cancer Epidemiology and Prevention Biomarkers. 10(6). 589–593. 1 indexed citations
20.
Jung, Sin‐Ho & Seung‐Ho Kang. (2001). Tests for 2×K contingency tables with clustered ordered categorical data. Statistics in Medicine. 20(5). 785–794. 6 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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