Woosuck Shin

6.3k total citations
254 papers, 5.4k citations indexed

About

Woosuck Shin is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Biomedical Engineering. According to data from OpenAlex, Woosuck Shin has authored 254 papers receiving a total of 5.4k indexed citations (citations by other indexed papers that have themselves been cited), including 188 papers in Electrical and Electronic Engineering, 130 papers in Materials Chemistry and 102 papers in Biomedical Engineering. Recurrent topics in Woosuck Shin's work include Gas Sensing Nanomaterials and Sensors (153 papers), Advanced Chemical Sensor Technologies (86 papers) and Advanced Thermoelectric Materials and Devices (61 papers). Woosuck Shin is often cited by papers focused on Gas Sensing Nanomaterials and Sensors (153 papers), Advanced Chemical Sensor Technologies (86 papers) and Advanced Thermoelectric Materials and Devices (61 papers). Woosuck Shin collaborates with scholars based in Japan, South Korea and China. Woosuck Shin's co-authors include Noriya Izu, Norimitsu Murayama, Ichiro Matsubara, Toshio Itoh, Maiko Nishibori, Takafumi Akamatsu, Masahiko Matsumiya, Shuzo Kanzaki, Fabin Qiu and Akihiro Tsuruta and has published in prestigious journals such as Journal of Applied Physics, Advanced Functional Materials and Journal of Power Sources.

In The Last Decade

Woosuck Shin

248 papers receiving 5.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Woosuck Shin Japan 41 3.4k 3.1k 2.0k 1.2k 802 254 5.4k
Noriya Izu Japan 40 3.1k 0.9× 2.7k 0.9× 1.7k 0.9× 1.3k 1.1× 808 1.0× 205 4.8k
Norimitsu Murayama Japan 36 2.2k 0.6× 2.4k 0.8× 1.1k 0.5× 722 0.6× 614 0.8× 181 4.2k
Wei Zheng China 48 4.6k 1.4× 4.0k 1.3× 2.2k 1.1× 1.3k 1.0× 722 0.9× 107 6.6k
A. Cirera Spain 38 3.5k 1.0× 2.6k 0.9× 2.0k 1.0× 1.1k 0.9× 744 0.9× 136 5.0k
Kyoung Jin Choi South Korea 38 3.8k 1.1× 4.0k 1.3× 1.9k 1.0× 704 0.6× 807 1.0× 111 6.3k
Yongming Hu China 35 3.1k 0.9× 2.4k 0.8× 1.7k 0.9× 909 0.7× 870 1.1× 198 5.0k
Yong Hyup Kim South Korea 31 2.6k 0.8× 1.8k 0.6× 1.4k 0.7× 318 0.3× 440 0.5× 93 4.3k
Yong‐Ho Choa South Korea 36 2.2k 0.7× 2.8k 0.9× 2.0k 1.0× 481 0.4× 860 1.1× 307 5.7k
Andreas Bund Germany 44 4.3k 1.3× 2.1k 0.7× 1.5k 0.8× 497 0.4× 877 1.1× 256 6.9k
Jyongsik Jang South Korea 52 3.6k 1.1× 3.9k 1.3× 1.9k 1.0× 509 0.4× 2.6k 3.3× 158 8.0k

Countries citing papers authored by Woosuck Shin

Since Specialization
Citations

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

Fields of papers citing papers by Woosuck Shin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Woosuck Shin

This figure shows the co-authorship network connecting the top 25 collaborators of Woosuck Shin. A scholar is included among the top collaborators of Woosuck 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 Woosuck Shin. Woosuck 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
2.
Itoh, Toshio, et al.. (2023). Machine-learning-assisted sensor array for detecting COVID-19 through simulated exhaled air. Sensors and Actuators B Chemical. 400. 134883–134883. 6 indexed citations
4.
Shin, Woosuck, et al.. (2023). Machine learning based analysis of metal support co-sintering process for solid oxide fuel cells. Ceramics International. 49(22). 36478–36489. 10 indexed citations
5.
Nomura, Katsuhiro, Hiroyuki Shimada, Yuki Yamaguchi, et al.. (2022). Machine learning based prediction of space group for Ba(Ce0.8-Zr )Y0.2O3 perovskite-type protonic conductors. Ceramics International. 49(3). 5058–5065. 13 indexed citations
6.
Nomura, Katsuhiro, Hiroyuki Shimada, Yuki Yamaguchi, et al.. (2022). Phase Transitions, Thermal Expansions, Chemical Expansions, and CO 2 Resistances of Ba(Ce 0.8- x Zr x Y 0.1 Yb 0.1 )O 3- δ (x = 0.1, 0.4) Perovskite-Type Proton Conductors. Journal of The Electrochemical Society. 169(2). 24516–24516. 19 indexed citations
7.
Zhang, Yuqiao, Hai Jun Cho, Masashi Mikami, et al.. (2021). Low thermal conductivity of SrTiO 3 −LaTiO 3 and SrTiO 3 −SrNbO 3 thermoelectric oxide solid solutions. Journal of the American Ceramic Society. 104(8). 4075–4085. 11 indexed citations
8.
Itoh, Toshio, T. Sato, Takafumi Akamatsu, & Woosuck Shin. (2019). Breath analysis using a spirometer and volatile organic compound sensor on driving simulator. Journal of Breath Research. 14(1). 16003–16003. 3 indexed citations
9.
Tsuruta, Akihiro, Katsuhiro Nomura, Masashi Mikami, et al.. (2018). Unusually Small Thermal Expansion of Ordered Perovskite Oxide CaCu3Ru4O12 with High Conductivity. Materials. 11(9). 1650–1650. 6 indexed citations
10.
Tsuruta, Akihiro, Toshio Itoh, Masashi Mikami, et al.. (2018). Trial of an All-Ceramic SnO2 Gas Sensor Equipped with CaCu3Ru4O12 Heater and Electrode. Materials. 11(6). 981–981. 10 indexed citations
11.
Shin, Woosuck, et al.. (2016). Device-Free Indoor Localization Based on Data Mining Classification Algorithms. Sensors and Materials. 637–637. 1 indexed citations
12.
Itoh, Toshio, Daiheon Lee, Tomoyo Goto, et al.. (2016). Analysis of Recovery Time of Pt-, Pd-, and Au-Loaded SnO2 Sensor Material with Nonanal as Large-Molecular-Weight Volatile Organic Compounds. Sensors and Materials. 1165–1165. 13 indexed citations
13.
Akamatsu, Takafumi, et al.. (2016). Effect of Noble Metal Addition on Co3O4-Based Gas Sensors for Selective NO Detection. Sensors and Materials. 1191–1191. 3 indexed citations
14.
Lin, Ding‐Bing, et al.. (2015). Room Occupancy Determination Using Multimodal Sensor Fusion. Sensors and Materials. 1–1. 1 indexed citations
15.
Itoh, Toshio, Ichiro Matsubara, Jun Tamaki, et al.. (2012). Effect of High-Humidity Aging on Performance of Tungsten Oxide-Type Aromatic Compound Sensors. Sensors and Materials. 13–13. 10 indexed citations
16.
Shin, Woosuck, Maiko Nishibori, & Ichiro Matsubara. (2011). Development of micro gas sensors. 87(12). 835–839. 1 indexed citations
17.
Shin, Woosuck, et al.. (2011). Thermoelectric hydrogen gas sensor - Technology to secure safety in hydrogen usage and international standardization of hydrogen gas sensor. 4(2). 92–99. 2 indexed citations
18.
Itoh, Toshio, Ichiro Matsubara, Yuichi Sakai, et al.. (2009). Gas-Sensing Properties of Tin Oxide-Based Volatile Organic Compound Sensors for Total Volatile Organic Compound Gases. Sensors and Materials. 251–251. 7 indexed citations
19.
Choi, Yeongsoo, Kazuki Tajima, Woosuck Shin, et al.. (2004). Planar catalytic combustor application for gas sensing. 277–277. 3 indexed citations
20.
Shin, Woosuck & Norimitsu Murayama. (1999). Li-Doped Nickel Oxide as a Thermoelectric Material. Japanese Journal of Applied Physics. 38(11B). L1336–L1336. 62 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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