Seonghoon Jang

1.1k total citations
20 papers, 961 citations indexed

About

Seonghoon Jang is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Seonghoon Jang has authored 20 papers receiving a total of 961 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Electrical and Electronic Engineering, 6 papers in Biomedical Engineering and 5 papers in Cellular and Molecular Neuroscience. Recurrent topics in Seonghoon Jang's work include Advanced Memory and Neural Computing (17 papers), Ferroelectric and Negative Capacitance Devices (7 papers) and Advanced Sensor and Energy Harvesting Materials (6 papers). Seonghoon Jang is often cited by papers focused on Advanced Memory and Neural Computing (17 papers), Ferroelectric and Negative Capacitance Devices (7 papers) and Advanced Sensor and Energy Harvesting Materials (6 papers). Seonghoon Jang collaborates with scholars based in South Korea, Japan and United States. Seonghoon Jang's co-authors include Gunuk Wang, Tae‐Wook Kim, Sanghyeon Choi, Minji Kang, Hu Young Jeong, Jong Chan Kim, Seonggil Ham, Jingon Jang, Sukjae Jang and Chul‐Ho Lee and has published in prestigious journals such as Advanced Materials, Nano Letters and ACS Nano.

In The Last Decade

Seonghoon Jang

20 papers receiving 946 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seonghoon Jang South Korea 13 869 402 265 178 177 20 961
Yanyun Ren China 13 787 0.9× 331 0.8× 229 0.9× 149 0.8× 141 0.8× 24 957
Huihuang Yang China 17 853 1.0× 302 0.8× 337 1.3× 236 1.3× 140 0.8× 32 935
Huiwu Mao China 18 785 0.9× 320 0.8× 203 0.8× 119 0.7× 227 1.3× 34 904
Changsong Gao China 19 918 1.1× 345 0.9× 264 1.0× 181 1.0× 212 1.2× 44 1.1k
Sanghyeon Choi South Korea 15 1.0k 1.2× 438 1.1× 272 1.0× 145 0.8× 144 0.8× 28 1.2k
Dingdong Xie China 14 1.1k 1.2× 524 1.3× 213 0.8× 120 0.7× 305 1.7× 18 1.2k
Adithi Krishnaprasad United States 13 900 1.0× 331 0.8× 187 0.7× 114 0.6× 357 2.0× 20 1.0k
Durjoy Dev United States 14 947 1.1× 326 0.8× 188 0.7× 126 0.7× 431 2.4× 19 1.1k
Wennan Hu China 12 740 0.9× 308 0.8× 153 0.6× 99 0.6× 265 1.5× 15 824

Countries citing papers authored by Seonghoon Jang

Since Specialization
Citations

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

Fields of papers citing papers by Seonghoon Jang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seonghoon Jang

This figure shows the co-authorship network connecting the top 25 collaborators of Seonghoon Jang. A scholar is included among the top collaborators of Seonghoon Jang 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 Seonghoon Jang. Seonghoon Jang 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.
Ham, Seonggil, Jingon Jang, Seonghoon Jang, et al.. (2024). Artificial neuromodulator–synapse mimicked by a three-terminal vertical organic ferroelectric barristor for fast and energy-efficient neuromorphic computing. Nano Energy. 124. 109435–109435. 9 indexed citations
2.
Jang, Seonghoon, Yongjun Kim, Jihoon Jeon, et al.. (2023). Three-terminal vertical ferroelectric synaptic barristor enabled by HZO/graphene heterostructure with rebound depolarization. Journal of Alloys and Compounds. 965. 171247–171247. 3 indexed citations
3.
Huh, Woong, Donghun Lee, Seonghoon Jang, et al.. (2023). Heterosynaptic MoS2 Memtransistors Emulating Biological Neuromodulation for Energy‐Efficient Neuromorphic Electronics. Advanced Materials. 35(24). e2211525–e2211525. 48 indexed citations
4.
Jang, Jingon, Sanghyeon Choi, Seonghoon Jang, et al.. (2022). A Learning‐Rate Modulable and Reliable TiOx Memristor Array for Robust, Fast, and Accurate Neuromorphic Computing. Advanced Science. 9(22). e2201117–e2201117. 49 indexed citations
5.
Jang, Jingon, Seonghoon Jang, Sanghyeon Choi, & Gunuk Wang. (2021). Run-off election-based decision method for the training and inference process in an artificial neural network. Scientific Reports. 11(1). 895–895. 1 indexed citations
6.
Kim, Youngwoo, Kyuho Lee, Junseok Lee, et al.. (2021). Bird-Inspired Self-Navigating Artificial Synaptic Compass. ACS Nano. 15(12). 20116–20126. 17 indexed citations
7.
Lee, Kyuho, Hyowon Han, Youngwoo Kim, et al.. (2021). Retina‐Inspired Structurally Tunable Synaptic Perovskite Nanocones. Advanced Functional Materials. 31(52). 76 indexed citations
8.
Choi, Sanghyeon, Jong Chan Kim, Hu Young Jeong, et al.. (2021). Energy-efficient three-terminal SiO memristor crossbar array enabled by vertical Si/graphene heterojunction barristor. Nano Energy. 84. 105947–105947. 42 indexed citations
9.
Lee, Kyuho, Hyowon Han, Jumi Park, et al.. (2021). Retina‐Inspired Structurally Tunable Synaptic Perovskite Nanocones (Adv. Funct. Mater. 52/2021). Advanced Functional Materials. 31(52). 4 indexed citations
10.
Ham, Seonggil, Minji Kang, Seonghoon Jang, et al.. (2020). One-dimensional organic artificial multi-synapses enabling electronic textile neural network for wearable neuromorphic applications. Science Advances. 6(28). 140 indexed citations
11.
Jang, Seonghoon, et al.. (2020). Deep Learning-Based Smart Meter Wattage Prediction Analysis Platform. International journal of advanced smart convergence. 9(4). 173–178. 1 indexed citations
12.
Lee, Kyuho, Seonghoon Jang, Kang Lib Kim, et al.. (2020). Artificially Intelligent Tactile Ferroelectric Skin. Advanced Science. 7(22). 2001662–2001662. 68 indexed citations
13.
Lee, Kyuho, Seonghoon Jang, Kang Lib Kim, et al.. (2020). AI Electronic Skin: Artificially Intelligent Tactile Ferroelectric Skin (Adv. Sci. 22/2020). Advanced Science. 7(22). 2 indexed citations
14.
Jang, Sukjae, Seonghoon Jang, Eun Hye Lee, et al.. (2018). Ultrathin Conformable Organic Artificial Synapse for Wearable Intelligent Device Applications. ACS Applied Materials & Interfaces. 11(1). 1071–1080. 135 indexed citations
15.
Choi, Sanghyeon, Seonghoon Jang, Jung‐Hwan Moon, et al.. (2018). A self-rectifying TaOy/nanoporous TaOx memristor synaptic array for learning and energy-efficient neuromorphic systems. NPG Asia Materials. 10(12). 1097–1106. 108 indexed citations
16.
Huh, Woong, Seonghoon Jang, Donghun Lee, et al.. (2018). Synaptic Barristor Based on Phase‐Engineered 2D Heterostructures. Advanced Materials. 30(35). e1801447–e1801447. 174 indexed citations
17.
Huh, Woong, Seonghoon Jang, Donghun Lee, et al.. (2018). 2D Materials: Synaptic Barristor Based on Phase‐Engineered 2D Heterostructures (Adv. Mater. 35/2018). Advanced Materials. 30(35). 3 indexed citations
18.
19.
Kim, Tae‐Wook, Seonghoon Jang, Nam Dong Kim, et al.. (2017). Structurally Engineered Nanoporous Ta2O5–x Selector-Less Memristor for High Uniformity and Low Power Consumption. ACS Applied Materials & Interfaces. 9(39). 34015–34023. 30 indexed citations
20.
Lee, Tae‐Ho, Hyun-Gyu Hwang, Seonghoon Jang, et al.. (2017). Low-Temperature-Grown KNbO3 Thin Films and Their Application to Piezoelectric Nanogenerators and Self-Powered ReRAM Device. ACS Applied Materials & Interfaces. 9(49). 43220–43229. 29 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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