Seungwon Shin

3.6k total citations
154 papers, 2.8k citations indexed

About

Seungwon Shin is a scholar working on Computational Mechanics, Biomedical Engineering and Surfaces, Coatings and Films. According to data from OpenAlex, Seungwon Shin has authored 154 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Computational Mechanics, 26 papers in Biomedical Engineering and 24 papers in Surfaces, Coatings and Films. Recurrent topics in Seungwon Shin's work include Fluid Dynamics and Heat Transfer (70 papers), Surface Modification and Superhydrophobicity (24 papers) and Fluid Dynamics Simulations and Interactions (22 papers). Seungwon Shin is often cited by papers focused on Fluid Dynamics and Heat Transfer (70 papers), Surface Modification and Superhydrophobicity (24 papers) and Fluid Dynamics Simulations and Interactions (22 papers). Seungwon Shin collaborates with scholars based in South Korea, France and United Kingdom. Seungwon Shin's co-authors include Damir Jurić, Youngsuk Nam, Jalel Chergui, S. I. Abdel‐Khalik, Hyun‐Sik Kim, Lyes Kahouadji, Choongyeop Lee, Virginie Daru, Omar K. Matar and Ji Hyun Kim and has published in prestigious journals such as Nature Communications, Applied Physics Letters and Journal of Fluid Mechanics.

In The Last Decade

Seungwon Shin

142 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seungwon Shin South Korea 29 1.5k 612 476 475 444 154 2.8k
Guoping Lian United Kingdom 29 736 0.5× 109 0.2× 444 0.9× 460 1.0× 299 0.7× 72 2.9k
R.G.M. van der Sman Netherlands 43 1.1k 0.8× 106 0.2× 496 1.0× 1.4k 2.9× 2.4k 5.4× 160 5.6k
Anurag Tripathi India 26 464 0.3× 35 0.1× 381 0.8× 257 0.5× 89 0.2× 118 2.2k
Jakob Søndergaard Jensen Denmark 40 283 0.2× 406 0.7× 100 0.2× 2.5k 5.2× 123 0.3× 119 6.5k
Michael K. Jensen United States 54 1.3k 0.9× 138 0.2× 1.5k 3.3× 1.2k 2.6× 112 0.3× 234 8.1k
H.M. Thompson United Kingdom 32 1.1k 0.7× 183 0.3× 74 0.2× 484 1.0× 58 0.1× 133 2.9k
Satoshi Kumagai Japan 20 138 0.1× 87 0.1× 355 0.7× 363 0.8× 99 0.2× 128 1.3k
Damiano Rossetti United Kingdom 15 168 0.1× 59 0.1× 62 0.1× 172 0.4× 327 0.7× 27 1.1k
Ching‐Hua Wang Taiwan 18 647 0.4× 57 0.1× 60 0.1× 343 0.7× 26 0.1× 59 1.4k
Deguo Wang China 31 94 0.1× 62 0.1× 112 0.2× 530 1.1× 145 0.3× 216 3.4k

Countries citing papers authored by Seungwon Shin

Since Specialization
Citations

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

Fields of papers citing papers by Seungwon Shin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seungwon Shin

This figure shows the co-authorship network connecting the top 25 collaborators of Seungwon Shin. A scholar is included among the top collaborators of Seungwon Shin 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 Seungwon Shin. Seungwon Shin 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.
Pati, A.R., et al.. (2025). Effect of surface curvature on drop impact forces on curved superhydrophobic surfaces. International Journal of Multiphase Flow. 191. 105304–105304.
2.
Valdés, Juan Pablo, Sibo Cheng, Lyes Kahouadji, et al.. (2024). Liquid–Liquid Dispersion Performance Prediction and Uncertainty Quantification Using Recurrent Neural Networks. Industrial & Engineering Chemistry Research. 63(17). 7853–7875. 7 indexed citations
4.
Kim, Seong Jin, et al.. (2024). Neural network-based regression for effective parametric study of micro-pin fin heat sinks. Physics of Fluids. 36(8). 2 indexed citations
5.
Ha, Taekyun, et al.. (2024). NUMERICAL INVESTIGATION OF CONTACT ANGLE EFFECT ON OIL-WATER SEPARATION FLOW PASSING THROUGH A POROUS STRUCTURE. Journal of computational fluids engineering. 29(4). 247–256. 1 indexed citations
6.
Kahouadji, Lyes, et al.. (2024). Drop encapsulation and bubble bursting in surfactant-laden flows in capillary channels. Physical Review Fluids. 9(3). 5 indexed citations
7.
Kahouadji, Lyes, et al.. (2021). Direct numerical simulations of transient turbulent jets: vortex-interface interactions. Journal of Fluid Mechanics. 922. 24 indexed citations
8.
Shin, Seungwon, et al.. (2020). Symmetry breaking of Worthington jets by gradients in liquid pool depth. Physics of Fluids. 32(11). 14 indexed citations
9.
Shin, Seungwon, et al.. (2020). Evaluation of Slope Stability of Reservoir Considering Heterogeneous Soil Properties. Korean Society of Hazard Mitigation. 20(6). 167–175.
10.
Craster, Richard V., Seungwon Shin, Jalel Chergui, et al.. (2017). Direct simulation of fluid-structure interaction with Blue. Bulletin of the American Physical Society. 1 indexed citations
11.
Shin, Seungwon, et al.. (2015). Preliminary Study for Development of Pattern Identification Tool of Chronic Cough. The Journal of Internal Korean Medicine. 36(1). 22–39. 8 indexed citations
12.
Ahn, Joon, et al.. (2009). NUMERICAL OPTIMIZATION OF TEMPERATURE DISTRIBUTION IN HRSG SYSTEM USING INLET GUIDE VANE. Journal of computational fluids engineering. 14(3). 1–8. 2 indexed citations
13.
Shin, Seungwon, et al.. (2008). Combined Effects of the Essential Oil from Eucalyptus globulus with Ketoconazole against Candida and Trichophyton Species. Natural Product Sciences. 14(1). 27–31. 3 indexed citations
14.
Shin, Seungwon, et al.. (2008). Analysis of Composition and Activity of Essential Oil from Chrysanthemum zawadskii var. latilobum and C. indicum against Antibiotic-Resistant Pathogenic Bacteria. Natural Product Sciences. 14(2). 138–142. 4 indexed citations
15.
Kim, Kyeong-Seop, Seungwon Shin, Jeong‐Whan Lee, & Heejung Choi. (2008). The Assessment of Dynamic Mental Stress with Wearable Heart Activity Monitoring System. The Transactions of The Korean Institute of Electrical Engineers. 57(6). 1109–1115. 7 indexed citations
16.
Shin, Seungwon, et al.. (2008). Noise Reduction and Estimating the Similarity of Ambulatory ECG Signals. The Transactions of The Korean Institute of Electrical Engineers. 57(3). 507–513. 1 indexed citations
17.
Shin, Seungwon, et al.. (2007). Combined Effects of the Essential Oil from Pelargonium graveolens with Antibiotics against Streptococcus pneumoniae. Natural Product Sciences. 13(4). 342–346. 6 indexed citations
18.
Shin, Seungwon. (2005). Antifungal Activities of Essential Oils from Glehnia littoralis Alone and in Combination with Ketoconazole. Natural Product Sciences. 11(2). 92–96. 2 indexed citations
19.
Shin, Seungwon. (2004). In vitro Inhibitory Activities of Essential Oils from Oenanthe javanica DC against Candida and Streptococcus species. Natural Product Sciences. 10(6). 325–329. 5 indexed citations
20.
Shin, Seungwon & Damir Jurić. (2000). Direct computations of solidification with fluid flow. APS. 53. 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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