Woo Young Kwon

467 total citations
32 papers, 389 citations indexed

About

Woo Young Kwon is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Woo Young Kwon has authored 32 papers receiving a total of 389 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 8 papers in Molecular Biology and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Woo Young Kwon's work include Lipid metabolism and biosynthesis (4 papers), Advanced biosensing and bioanalysis techniques (4 papers) and Reinforcement Learning in Robotics (3 papers). Woo Young Kwon is often cited by papers focused on Lipid metabolism and biosynthesis (4 papers), Advanced biosensing and bioanalysis techniques (4 papers) and Reinforcement Learning in Robotics (3 papers). Woo Young Kwon collaborates with scholars based in South Korea, United States and Canada. Woo Young Kwon's co-authors include Il Hong Suh, Ki Soo Park, Kalimuthu Kalishwaralal, Hye Young Kim, Yoo Jin Oh, Seokjoon Kim, Young Hyun Yoo, Ju Yong Bae, Seung Hee Yoo and Mihwa Lee and has published in prestigious journals such as Cancer Research, The FASEB Journal and International Journal of Molecular Sciences.

In The Last Decade

Woo Young Kwon

30 papers receiving 378 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Woo Young Kwon South Korea 12 181 59 55 50 47 32 389
Ruijia Li China 12 114 0.6× 47 0.8× 49 0.9× 55 1.1× 83 1.8× 39 371
Zhenyao Yu China 6 110 0.6× 79 1.3× 23 0.4× 30 0.6× 37 0.8× 9 315
Shiwei Zhang China 14 100 0.6× 85 1.4× 36 0.7× 114 2.3× 20 0.4× 55 641
Xingyan Li China 13 478 2.6× 39 0.7× 37 0.7× 19 0.4× 71 1.5× 49 766
Yuxiang Cui United States 8 268 1.5× 13 0.2× 14 0.3× 19 0.4× 76 1.6× 21 432
Yifeng Liu China 12 207 1.1× 36 0.6× 27 0.5× 62 1.2× 34 0.7× 31 431
Heming Chen China 14 268 1.5× 16 0.3× 28 0.5× 24 0.5× 191 4.1× 25 588
Mingwu Chen China 12 195 1.1× 18 0.3× 15 0.3× 13 0.3× 95 2.0× 41 448
Martin Bak Denmark 10 191 1.1× 36 0.6× 117 2.1× 18 0.4× 14 0.3× 17 567
Agnieszka Rybarczyk Poland 12 237 1.3× 25 0.4× 29 0.5× 15 0.3× 39 0.8× 53 392

Countries citing papers authored by Woo Young Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Woo Young Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Woo Young Kwon. 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 Woo Young Kwon. The network helps show where Woo Young Kwon may publish in the future.

Co-authorship network of co-authors of Woo Young Kwon

This figure shows the co-authorship network connecting the top 25 collaborators of Woo Young Kwon. A scholar is included among the top collaborators of Woo Young Kwon 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 Woo Young Kwon. Woo Young Kwon 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.
Kang, Incheon, Woo Young Kwon, & Sung Hwan Lee. (2024). Abstract 7364: Comprehensive multi-omics analysis for resectable hepatocellular carcinoma uncovers biomarkers to predict microvascular invasion. Cancer Research. 84(6_Supplement). 7364–7364. 1 indexed citations
2.
Baek, Yang Hyun, Woo Young Kwon, Sunghwan Suh, et al.. (2023). Pharmacological Prevention of Ectopic Erythrophagocytosis by Cilostazol Mitigates Ferroptosis in NASH. International Journal of Molecular Sciences. 24(16). 12862–12862. 9 indexed citations
3.
Kalishwaralal, Kalimuthu, et al.. (2020). Characterization of Rajath Bhasma and Evaluation of Its Toxicity in Zebrafish Embryos and Its Antimicrobial Activity. Journal of Microbiology and Biotechnology. 30(6). 920–925. 2 indexed citations
4.
Kwon, Woo Young, Kalimuthu Kalishwaralal, Yonghwan Kim, et al.. (2019). Melamine-promoted formation of bright and stable DNA–silver nanoclusters and their antimicrobial properties. Journal of Materials Chemistry B. 7(15). 2512–2517. 11 indexed citations
5.
Kim, Seokjoon, Jung Ho Kim, Woo Young Kwon, et al.. (2019). Synthesis of DNA-templated copper nanoparticles with enhanced fluorescence stability for cellular imaging. Microchimica Acta. 186(7). 479–479. 30 indexed citations
6.
Kalishwaralal, Kalimuthu, Woo Young Kwon, & Ki Soo Park. (2019). A simple approach for rapid and cost-effective quantification of extracellular vesicles using a fluorescence polarization technique. Journal of Biological Engineering. 13(1). 31–31. 26 indexed citations
7.
Kwon, Woo Young, et al.. (2019). Target-Induced Aggregation of Gold Nanoparticles for Colorimetric Detection of Bisphenol A. Journal of Nanomaterials. 2019. 1–7. 23 indexed citations
8.
Kwon, Woo Young, Byung Seok, Seokjoon Kim, et al.. (2019). Fluorescence polarization-based detection of cancer-related mutations using target-initiated rolling circle amplification. The Analyst. 144(14). 4149–4152. 11 indexed citations
9.
Oh, Yoo Jin, Hye Young Kim, Sunghwan Suh, et al.. (2018). Cilostazol Improves HFD-Induced Hepatic Steatosis by Upregulating Hepatic STAMP2 Expression through AMPK. Molecular Pharmacology. 94(6). 1401–1411. 20 indexed citations
10.
Kim, Hye Young, Woo Young Kwon, Sung Won Lee, et al.. (2018). Polychlorinated biphenyl 138 exposure-mediated lipid droplet enlargement endows adipocytes with resistance to TNF-α-induced cell death. Toxicology Letters. 292. 55–62. 12 indexed citations
11.
Lee, Sung Won, Jee Hyun Rho, Sang Yeob Lee, et al.. (2018). Dietary fat-associated osteoarthritic chondrocytes gain resistance to lipotoxicity through PKCK2/STAMP2/FSP27. Bone Research. 6(1). 20–20. 24 indexed citations
12.
Kwon, Woo Young, Jun Seok Park, Kwang Jin Kim, et al.. (2018). The use of a 2-aminopurine-containing split G-quadruplex for sequence-specific DNA detection. Artificial Cells Nanomedicine and Biotechnology. 46(sup3). 950–955. 8 indexed citations
13.
Kim, Hye Young, Woo Young Kwon, Yoo Jin Oh, et al.. (2016). Polychlorinated biphenyls exposure-induced insulin resistance is mediated by lipid droplet enlargement through Fsp27. Archives of Toxicology. 91(6). 2353–2363. 34 indexed citations
14.
15.
Kwon, Woo Young, et al.. (2013). Imitation Learning of Bimanual Manipulation Skills Considering Both Position and Force Trajectory. The Journal of Korea Robotics Society. 8(1). 20–28. 1 indexed citations
16.
Kwon, Woo Young & Il Hong Suh. (2011). Towards proactive assistant robots for human assembly tasks. 175–176. 7 indexed citations
17.
Kwon, Woo Young, Il Hong Suh, & Sanghoon Lee. (2011). SSPQL: Stochastic shortest path-based Q-learning. International Journal of Control Automation and Systems. 9(2). 328–338. 9 indexed citations
18.
Lee, Sanghoon, Il Hong Suh, & Woo Young Kwon. (2008). A Motivation-Based Action-Selection-Mechanism Involving Reinforcement Learning. International Journal of Control Automation and Systems. 6(6). 904–914. 5 indexed citations
19.
Kwon, Woo Young, et al.. (2004). A reinforcement learning approach involving a shortest path finding algorithm. 1. 436–441. 6 indexed citations
20.
Suh, Il Hong, Woo Young Kwon, & Sanghoon Lee. (2003). A Novel Action Selection Mechanism for Intelligent Service Robots. 제어로봇시스템학회 국제학술대회 논문집. 2027–2032. 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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