Hwan Pyo Moon

48 total papers · 1.1k total citations
35 papers, 815 citations indexed

About

Hwan Pyo Moon is a scholar working on Computational Mechanics, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hwan Pyo Moon has authored 35 papers receiving a total of 815 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computational Mechanics, 13 papers in Computer Graphics and Computer-Aided Design and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hwan Pyo Moon's work include Advanced Numerical Analysis Techniques (27 papers), Computer Graphics and Visualization Techniques (11 papers) and Advanced Vision and Imaging (7 papers). Hwan Pyo Moon is often cited by papers focused on Advanced Numerical Analysis Techniques (27 papers), Computer Graphics and Visualization Techniques (11 papers) and Advanced Vision and Imaging (7 papers). Hwan Pyo Moon collaborates with scholars based in South Korea, United States and China. Hwan Pyo Moon's co-authors include Hyeong In Choi, Sung Woo Choi, Rida T. Farouki, Bahram Ravani, Chang Yong Han, Kyeong Hah Roh, Tapan K. Sarkar, Yu Zhang, Wenling Gu and Tae‐Wan Kim and has published in prestigious journals such as Applied Mathematics and Computation, Pacific Journal of Mathematics and Computer-Aided Design.

In The Last Decade

Hwan Pyo Moon

33 papers receiving 788 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Hwan Pyo Moon 588 311 190 159 133 35 815
Martín Peternell 528 0.9× 281 0.9× 127 0.7× 89 0.6× 111 0.8× 29 709
Alessandra Sestini 660 1.1× 120 0.4× 143 0.8× 212 1.3× 103 0.8× 63 828
C. Andrew Neff 549 0.9× 251 0.8× 126 0.7× 168 1.1× 92 0.7× 16 708
Ronald Goldman 730 1.2× 369 1.2× 201 1.1× 126 0.8× 55 0.4× 61 996
Hyeong In Choi 511 0.9× 255 0.8× 168 0.9× 137 0.9× 382 2.9× 39 1.1k
Chun-Gang Zhu 481 0.8× 151 0.5× 56 0.3× 62 0.4× 62 0.5× 80 703
Boris Springborn 628 1.1× 521 1.7× 164 0.9× 46 0.3× 141 1.1× 22 889
Knut Mørken 653 1.1× 232 0.7× 253 1.3× 174 1.1× 15 0.1× 32 848
Fujio Yamaguchi 524 0.9× 276 0.9× 205 1.1× 157 1.0× 11 0.1× 32 813
John A. Roulier 473 0.8× 146 0.5× 66 0.3× 125 0.8× 30 0.2× 56 757

Countries citing papers authored by Hwan Pyo Moon

Since Specialization
Citations

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

Fields of papers citing papers by Hwan Pyo Moon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hwan Pyo Moon. 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 Hwan Pyo Moon. The network helps show where Hwan Pyo Moon may publish in the future.

Co-authorship network of co-authors of Hwan Pyo Moon

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

All Works

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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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