Chanyoung Park

2.0k citations
57 papers · 1.4k indexed · 1 hit paper · h-index 13

Chanyoung Park

53 papers receiving 1.4k citations

Hit Papers

Convolutional Matrix Factorization for Document Context-A...5212016202620192022100200300400500

Peers

Chanyoung Park
Comparison fields: 5 of 94
  • Statistics, Probability and Uncertainty 336
  • Information Systems 588
  • Computational Theory and Mathematics 339
  • Management Science and Operations Research 216
  • Artificial Intelligence 554
Replace Nicola Mazzocca with:
Nicola Mazzocca Italy
Hemant Kumar Singh Australia
Kenneth W. Bauer United States
Robert Kennes Belgium
Zaer S. Abo‐Hammour Jordan
Éric Lefèvre France
Dominic Grenier Canada
Zhong Yuan China
Edwin M. Knorr Canada
Dawei Zhan China
Chanyoung Park relative to Nicola Mazzocca Italy Nicola Mazzocca's profile →
Citations per field
00.5×10×
Nicola Mazzocca · 1×
Citations per year

Countries citing papers authored by Chanyoung Park

Since Specialization
Citations

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

Fields of papers citing papers by Chanyoung Park

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Chanyoung Park, 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 Chanyoung Park Line = papers co-authored together Chanyoung Park links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20250
4 20243
5 202414
6 20246
7 20241
8 202310
9 202334
10 20235
11 202311
12 202341
13 20232
14 20231
15 202330
16 20214
17 201916
18
Effect of Finite Particle Size on Convergence of Point Particle Models in Euler-Lagrange Multiphase Dispersed Flow
20172
19 2016172
20 20104

About Chanyoung Park

Chanyoung Park is a scholar working on Statistics, Probability and Uncertainty, Aerospace Engineering and Computational Theory and Mathematics, having authored 57 papers that have together received 1.4k indexed citations. Recurring topics across this work include Probabilistic and Robust Engineering Design (16 papers), Advanced Multi-Objective Optimization Algorithms (12 papers), UAV Applications and Optimization (8 papers), Optimal Experimental Design Methods (7 papers), Combustion and Detonation Processes (6 papers), Recommender Systems and Techniques (5 papers), Distributed Control Multi-Agent Systems (5 papers) and Particle Dynamics in Fluid Flows (5 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (336 citations), Information Systems (588 citations) and Computational Theory and Mathematics (339 citations). Chanyoung Park has collaborated with scholars based in United States, South Korea and China. Frequent co-authors include Raphael T. Haftka, Nam Ho Kim, Hwanjo Yu, Yejin Kim, Jinoh Oh, Sungyoung Lee, M. Giselle Fernández-Godino, Soohyun Park, Joongheon Kim and Soyi Jung. Their work appears in journals such as IEEE Access, IEEE Communications Magazine and AIAA Journal.

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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