Won-Mook Kang

509 total citations
23 papers, 399 citations indexed

About

Won-Mook Kang is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Cognitive Neuroscience. According to data from OpenAlex, Won-Mook Kang has authored 23 papers receiving a total of 399 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Electrical and Electronic Engineering, 8 papers in Cellular and Molecular Neuroscience and 8 papers in Cognitive Neuroscience. Recurrent topics in Won-Mook Kang's work include Advanced Memory and Neural Computing (17 papers), Neural dynamics and brain function (8 papers) and Ferroelectric and Negative Capacitance Devices (8 papers). Won-Mook Kang is often cited by papers focused on Advanced Memory and Neural Computing (17 papers), Neural dynamics and brain function (8 papers) and Ferroelectric and Negative Capacitance Devices (8 papers). Won-Mook Kang collaborates with scholars based in South Korea and United States. Won-Mook Kang's co-authors include Jong‐Ho Lee, Sung Yun Woo, Jong‐Ho Bae, Soochang Lee, Chul-Heung Kim, Byung‐Gook Park, In-Tak Cho, Suhwan Lim, Dongseok Kwon and Jangsaeng Kim and has published in prestigious journals such as Applied Physics Letters, IEEE Access and IEEE Transactions on Electron Devices.

In The Last Decade

Won-Mook Kang

23 papers receiving 390 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Won-Mook Kang South Korea 12 355 104 103 86 81 23 399
Harikrishnan Ravichandran United States 11 252 0.7× 113 1.1× 56 0.5× 39 0.5× 54 0.7× 19 351
Sarbashis Das United States 7 232 0.7× 85 0.8× 72 0.7× 52 0.6× 43 0.5× 7 290
Keji Zhou China 9 351 1.0× 75 0.7× 93 0.9× 43 0.5× 68 0.8× 31 392
Kyung Kyu Min South Korea 14 483 1.4× 105 1.0× 107 1.0× 31 0.4× 54 0.7× 36 519
Jeeson Kim South Korea 10 438 1.2× 54 0.5× 166 1.6× 44 0.5× 48 0.6× 21 520
Shengliang Cheng China 6 255 0.7× 137 1.3× 88 0.9× 25 0.3× 61 0.8× 8 341
Jinwoo Noh South Korea 8 460 1.3× 154 1.5× 181 1.8× 93 1.1× 33 0.4× 14 512
Bomin Joo South Korea 4 522 1.5× 125 1.2× 152 1.5× 110 1.3× 199 2.5× 7 574

Countries citing papers authored by Won-Mook Kang

Since Specialization
Citations

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

Fields of papers citing papers by Won-Mook Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Won-Mook Kang. 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 Won-Mook Kang. The network helps show where Won-Mook Kang may publish in the future.

Co-authorship network of co-authors of Won-Mook Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Won-Mook Kang. A scholar is included among the top collaborators of Won-Mook Kang 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 Won-Mook Kang. Won-Mook Kang 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.
Park, Minkyu, Won-Mook Kang, Ryun‐Han Koo, et al.. (2024). NOR-Type Flash Array Based on Four-Terminal TFT Synaptic Devices Capable of Selective Program/Erase Exploiting Fowler-Nordheim Tunneling. IEEE Electron Device Letters. 45(6). 1000–1003. 1 indexed citations
2.
Kwon, Dongseok, Minkyu Park, Won-Mook Kang, et al.. (2023). Hardware-Based Ternary Neural Network Using AND-Type Poly-Si TFT Array and Its Optimization Guideline. IEEE Transactions on Electron Devices. 70(8). 4206–4212. 2 indexed citations
3.
Kwon, Dongseok, et al.. (2022). Neuron Circuits for Low-Power Spiking Neural Networks Using Time-To-First-Spike Encoding. IEEE Access. 10. 24444–24455. 19 indexed citations
4.
Woo, Sung Yun, Won-Mook Kang, Soochang Lee, et al.. (2022). Demonstration of integrate-and-fire neuron circuit for spiking neural networks. Solid-State Electronics. 198. 108481–108481. 4 indexed citations
5.
Kang, Won-Mook, Dongseok Kwon, Sung Yun Woo, et al.. (2021). Hardware-Based Spiking Neural Network Using a TFT-Type AND Flash Memory Array Architecture Based on Direct Feedback Alignment. IEEE Access. 9. 73121–73132. 11 indexed citations
6.
Kim, Jangsaeng, Dongseok Kwon, Sung Yun Woo, et al.. (2021). On-chip trainable hardware-based deep Q-networks approximating a backpropagation algorithm. Neural Computing and Applications. 33(15). 9391–9402. 8 indexed citations
7.
Woo, Sung Yun, Dongseok Kwon, Won-Mook Kang, et al.. (2020). Low-Power and High-Density Neuron Device for Simultaneous Processing of Excitatory and Inhibitory Signals in Neuromorphic Systems. IEEE Access. 8. 202639–202647. 18 indexed citations
8.
Kim, Jangsaeng, Dongseok Kwon, Sung Yun Woo, et al.. (2020). Hardware-based spiking neural network architecture using simplified backpropagation algorithm and homeostasis functionality. Neurocomputing. 428. 153–165. 16 indexed citations
9.
Kim, Jangsaeng, Chul-Heung Kim, Sung Yun Woo, et al.. (2019). Initial synaptic weight distribution for fast learning speed and high recognition rate in STDP-based spiking neural network. Solid-State Electronics. 165. 107742–107742. 8 indexed citations
10.
Lee, Jong‐Ho, Sung Yun Woo, Sung‐Tae Lee, et al.. (2019). Review of candidate devices for neuromorphic applications. 22–27. 3 indexed citations
11.
Kang, Won-Mook, In-Tak Cho, Jeongkyun Roh, Changhee Lee, & Jong‐Ho Lee. (2019). Low-Frequency Noise Characteristics in Multi-Layer WSe2 Field Effect Transistors with Different Contact Metals. Journal of Nanoscience and Nanotechnology. 19(10). 6422–6428. 2 indexed citations
12.
Woo, Sung Yun, Jangsaeng Kim, Won-Mook Kang, et al.. (2019). Implementation of homeostasis functionality in neuron circuit using double-gate device for spiking neural network. Solid-State Electronics. 165. 107741–107741. 17 indexed citations
13.
Woo, Sung Yun, Won-Mook Kang, Jangsaeng Kim, et al.. (2019). Analyzation of Positive Feedback device with Steep Subthreshold Swing Characteristics in 14 nm FinFET Technology. 404–406. 1 indexed citations
14.
15.
Kim, Chul-Heung, Suhwan Lim, Sung Yun Woo, et al.. (2018). Emerging memory technologies for neuromorphic computing. Nanotechnology. 30(3). 32001–32001. 70 indexed citations
16.
Kim, Chul-Heung, Soochang Lee, Sung Yun Woo, et al.. (2018). Demonstration of Unsupervised Learning With Spike-Timing-Dependent Plasticity Using a TFT-Type NOR Flash Memory Array. IEEE Transactions on Electron Devices. 65(5). 1774–1780. 52 indexed citations
17.
Woo, Sung Yun, Won-Mook Kang, Soochang Lee, et al.. (2018). A Split-Gate Positive Feedback Device With an Integrate-and-Fire Capability for a High-Density Low-Power Neuron Circuit. Frontiers in Neuroscience. 12. 704–704. 31 indexed citations
18.
Kang, Won-Mook, Sung‐Tae Lee, In-Tak Cho, et al.. (2017). Multi-layer WSe 2 field effect transistor with improved carrier-injection contact by using oxygen plasma treatment. Solid-State Electronics. 140. 2–7. 43 indexed citations
19.
Hong, Yoonki, Won-Mook Kang, In-Tak Cho, et al.. (2017). Gas-Sensing Characteristics of Exfoliated WSe2 Field-Effect Transistors. Journal of Nanoscience and Nanotechnology. 17(5). 3151–3154. 40 indexed citations
20.
Park, Jun‐Mo, In-Tak Cho, Won-Mook Kang, Byung‐Gook Park, & Jong‐Ho Lee. (2016). Elimination of the gate and drain bias stresses in I–V characteristics of WSe2 FETs by using dual channel pulse measurement. Applied Physics Letters. 109(5). 10 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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