Cheol‐Min Park

547 total citations
26 papers, 283 citations indexed

About

Cheol‐Min Park is a scholar working on Artificial Intelligence, Information Systems and Computational Theory and Mathematics. According to data from OpenAlex, Cheol‐Min Park has authored 26 papers receiving a total of 283 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 7 papers in Information Systems and 5 papers in Computational Theory and Mathematics. Recurrent topics in Cheol‐Min Park's work include Coding theory and cryptography (9 papers), Cryptography and Residue Arithmetic (7 papers) and Cryptography and Data Security (5 papers). Cheol‐Min Park is often cited by papers focused on Coding theory and cryptography (9 papers), Cryptography and Residue Arithmetic (7 papers) and Cryptography and Data Security (5 papers). Cheol‐Min Park collaborates with scholars based in South Korea, United States and Canada. Cheol‐Min Park's co-authors include Kyung‐Ah Shim, Eunjeong Lee, Young-Ran Lee, Hyang-Sook Lee, Sang‐Hee Lee, Seongan Lim, Hoon Hong, Sang‐Bin Lee, Hwajeong Seo and Duck Young Kim and has published in prestigious journals such as IEEE Transactions on Information Theory, IEEE Access and IEEE Internet of Things Journal.

In The Last Decade

Cheol‐Min Park

21 papers receiving 265 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cheol‐Min Park South Korea 7 183 139 110 28 28 26 283
Zhi Hu China 8 200 1.1× 81 0.6× 168 1.5× 62 2.2× 32 1.1× 21 283
Daniel W. Brown United States 6 201 1.1× 127 0.9× 164 1.5× 39 1.4× 24 0.9× 11 339
Hervé Sibert France 6 90 0.5× 109 0.8× 82 0.7× 51 1.8× 27 1.0× 9 247
Patrick Longa United States 11 245 1.3× 35 0.3× 214 1.9× 74 2.6× 29 1.0× 24 327
Nick Howgrave-Graham United States 6 164 0.9× 82 0.6× 60 0.5× 42 1.5× 81 2.9× 9 229
Daniel V. Bailey United States 8 110 0.6× 45 0.3× 129 1.2× 27 1.0× 25 0.9× 14 189
Gunnar Gaubatz United States 5 147 0.8× 122 0.9× 75 0.7× 46 1.6× 19 0.7× 8 242
Jeffrey Young United States 9 45 0.2× 87 0.6× 36 0.3× 27 1.0× 20 0.7× 45 173
Kamil Saraç United States 12 151 0.8× 344 2.5× 32 0.3× 17 0.6× 53 1.9× 50 400
Aleksandra Mileva North Macedonia 8 136 0.7× 107 0.8× 43 0.4× 88 3.1× 40 1.4× 32 256

Countries citing papers authored by Cheol‐Min Park

Since Specialization
Citations

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

Fields of papers citing papers by Cheol‐Min Park

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cheol‐Min Park. 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 Cheol‐Min Park. The network helps show where Cheol‐Min Park may publish in the future.

Co-authorship network of co-authors of Cheol‐Min Park

This figure shows the co-authorship network connecting the top 25 collaborators of Cheol‐Min Park. A scholar is included among the top collaborators of Cheol‐Min Park 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 Cheol‐Min Park. Cheol‐Min Park 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.
Lee, Sang‐Hee & Cheol‐Min Park. (2024). A New Perspective on Shape and Distribution: Branch Length Similarity Entropy Approach. IEEE Access. 12. 137259–137267.
2.
Lee, Sang‐Hee & Cheol‐Min Park. (2023). A novel shape augmentation approach in training neural networks using Branch Length Similarity entropy. Physica A Statistical Mechanics and its Applications. 627. 129124–129124. 1 indexed citations
3.
Lee, Sang‐Hee, Sang‐Hee Lee, Cheol‐Min Park, Sang‐Bin Lee, & Sang‐Bin Lee. (2023). Effects of the surface irregularity of termite tunnels on food transport efficiency: a simulation study. Journal of Insect Science. 23(2). 1 indexed citations
4.
Lee, Sang‐Hee, Sang‐Hee Lee, Cheol‐Min Park, Sang‐Bin Lee, & Sang‐Bin Lee. (2022). Exploring the efficiency of termite food transportation in a sinusoidal-shaped tunnel. Ecological Modelling. 474. 110180–110180. 3 indexed citations
5.
Lee, Sang‐Hee & Cheol‐Min Park. (2022). Characteristics of Peak and Cliff in Branch Length Similarity Entropy Profiles for Binary Time-Series and Their Application. IEEE Access. 10. 107259–107268. 2 indexed citations
6.
Lee, Sang‐Hee & Cheol‐Min Park. (2021). Novel Features for Binary Time Series Based on Branch Length Similarity Entropy. Entropy. 23(4). 480–480. 2 indexed citations
7.
Lee, Sang‐Hee & Cheol‐Min Park. (2021). A New Measure to Characterize the Self-Similarity of Binary Time Series and its Application. IEEE Access. 9. 73799–73807. 3 indexed citations
8.
Lee, Sang‐Hee & Cheol‐Min Park. (2021). The effect of hunter-wild boar interactions and landscape heterogeneity on wild boar population size: A simulation study. Ecological Modelling. 464. 109847–109847. 1 indexed citations
9.
Lee, Sang‐Hee, et al.. (2020). A New Measure to Characterize the Degree of Self-Similarity of a Shape and Its Applicability. Entropy. 22(9). 1061–1061. 5 indexed citations
10.
Shim, Kyung‐Ah, et al.. (2020). An Efficient MQ-Signature Scheme Based on Sparse Polynomials. IEEE Access. 8. 26257–26265.
11.
Shim, Kyung‐Ah, et al.. (2017). Cryptanalysis of RGB, a mixed multivariate signature scheme. Finite Fields and Their Applications. 45. 406–421. 2 indexed citations
12.
Park, Cheol‐Min. (2017). Cryptanalysis of Matrix-based UOV. Finite Fields and Their Applications. 50. 209–221. 4 indexed citations
13.
Park, Cheol‐Min, et al.. (2014). The Relationship between Leader-Member Exchange and Organizational Commitment with Psychological Empowerment as a Mediator in the Public Organization. 14(4). 35–58. 1 indexed citations
14.
Lim, Seongan, Eunjeong Lee, & Cheol‐Min Park. (2013). Equivalent public keys and a key substitution attack on the schemes from vector decomposition. Security and Communication Networks. 7(8). 1274–1282. 4 indexed citations
15.
Lee, Hyang-Sook & Cheol‐Min Park. (2012). CONSTRUCTING PAIRING-FRIENDLY CURVES WITH VARIABLE CM DISCRIMINANT. Bulletin of the Korean Mathematical Society. 49(1). 75–88. 1 indexed citations
16.
Hong, Hoon, Eunjeong Lee, Hyang-Sook Lee, & Cheol‐Min Park. (2012). Maximum gap in (inverse) cyclotomic polynomial. Journal of Number Theory. 132(10). 2297–2315. 9 indexed citations
17.
Lee, Eunjeong, Hyang-Sook Lee, & Cheol‐Min Park. (2009). Efficient and Generalized Pairing Computation on Abelian Varieties. IEEE Transactions on Information Theory. 55(4). 1793–1803. 66 indexed citations
18.
Kim, Jong-Taek, et al.. (2007). Survey on the actual injured condition and wintery ecology of Black vulture(Aegypius monachus). Korean Journal of Veterinary Service. 30(3). 467–472.
19.
Kim, Duck Young & Cheol‐Min Park. (2007). Double Indirect Access: Efficient Peer-to-Peer Object Lookup Protocol in Location-Aware Mobile Ad Hoc Networks. IEICE Transactions on Communications. E90-B(4). 799–808. 1 indexed citations
20.
Park, Cheol‐Min, et al.. (2002). A Comparative Study of the Design Software Systems from the View Point of Optimization. Transactions of the Korean Society of Mechanical Engineers A. 26(1). 83–94. 1 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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