Pilwon Kim

23 papers receiving 240 citations

Peers

Pilwon Kim
Comparison fields: 5 of 73
  • Numerical Analysis 44
  • Statistical and Nonlinear Physics 72
  • Modeling and Simulation 23
  • Computational Mechanics 45
  • Physical and Theoretical Chemistry 10
Replace Tomáš Vejchodský with:
Tomáš Vejchodský Czechia
Tadas Meškauskas Lithuania
Beverly H. West United States
Felix Sadyrbaev Latvia
Grégory Faye France
Manoj Gopalkrishnan India
Warren Weckesser United States
M. C. Mariani Argentina
Н. Х. Розов Russia
Nikos I. Kavallaris United Kingdom
Pilwon Kim relative to Tomáš Vejchodský Czechia Tomáš Vejchodský's profile →
Citations per field
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Tomáš Vejchodský · 1×
Citations per year

Countries citing papers authored by Pilwon Kim

Since Specialization
Citations

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

Fields of papers citing papers by Pilwon Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside Pilwon Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Pilwon Kim Line = papers co-authored together Pilwon Kim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200974
2 200724
3
200423
4 201721
5 200720
6 202014
7 201211
8 20139
9 20188
10 20227
11 20206
12 20194
13 20214
14 20143
15 20233
16 20223
17 20123
18 20252
19
Fast Probability Generating Function Method for Stochastic Chemical Reaction Networks
20142
20 20222

About Pilwon Kim

Pilwon Kim is a scholar working on Cognitive Neuroscience, Statistical and Nonlinear Physics, Molecular Biology, Artificial Intelligence and Numerical Analysis, having authored 27 papers that have together received 247 indexed citations. Recurring topics across this work include Neural dynamics and brain function (7 papers), Neural Networks and Reservoir Computing (4 papers), Numerical methods for differential equations (4 papers), Gene Regulatory Network Analysis (4 papers), Nonlinear Waves and Solitons (3 papers), Neuroscience and Neuropharmacology Research (3 papers), Advanced Memory and Neural Computing (3 papers) and Ecosystem dynamics and resilience (3 papers). The work is most often cited by research in Numerical Analysis (44 citations), Statistical and Nonlinear Physics (72 citations), Modeling and Simulation (23 citations), Computational Mechanics (45 citations) and Physical and Theoretical Chemistry (10 citations). Pilwon Kim has collaborated with scholars based in South Korea and United States. Frequent co-authors include Chang Hyeong Lee, Kyeong-Hun Kim, Peter J. Olver, Perry H. Leo, Chun Sang Yoo, Yongbiao Yang, Jaeup U. Kim, Soyeong Jeong, Yunho Kim and Bongsoo Jang. Their work appears in journals such as Chaos An Interdisciplinary Journal of Nonlinear Science, Soft Matter, The Journal of Chemical Physics, Chaos Solitons & Fractals and Complexity.

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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