Soonwan Kwon

838 total citations · 1 hit paper
12 papers, 570 citations indexed

About

Soonwan Kwon is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Soonwan Kwon has authored 12 papers receiving a total of 570 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Electrical and Electronic Engineering, 2 papers in Artificial Intelligence and 1 paper in Computer Networks and Communications. Recurrent topics in Soonwan Kwon's work include Ferroelectric and Negative Capacitance Devices (9 papers), Advanced Memory and Neural Computing (9 papers) and Semiconductor materials and devices (5 papers). Soonwan Kwon is often cited by papers focused on Ferroelectric and Negative Capacitance Devices (9 papers), Advanced Memory and Neural Computing (9 papers) and Semiconductor materials and devices (5 papers). Soonwan Kwon collaborates with scholars based in South Korea, United States and Belgium. Soonwan Kwon's co-authors include Sungmeen Myung, Hyunsoo Kim, Sang Joon Kim, Seung Keun Yoon, Yong-Min Ju, Hyungwoo Lee, Shin-Hee Han, Yoon-Jong Song, Donhee Ham and G.H. Koh and has published in prestigious journals such as Nature, IEEE Journal of Solid-State Circuits and Frontiers in Neuroscience.

In The Last Decade

Soonwan Kwon

10 papers receiving 558 citations

Hit Papers

A crossbar array of magnetoresistive memory devices for i... 2022 2026 2023 2024 2022 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Soonwan Kwon South Korea 7 495 114 97 63 60 12 570
Sungmeen Myung South Korea 6 463 0.9× 106 0.9× 94 1.0× 54 0.9× 59 1.0× 9 526
Wooseok Yi South Korea 8 429 0.9× 141 1.2× 96 1.0× 54 0.9× 54 0.9× 16 542
Seung Keun Yoon South Korea 6 401 0.8× 98 0.9× 95 1.0× 57 0.9× 25 0.4× 11 494
Hyungwoo Lee South Korea 4 364 0.7× 91 0.8× 94 1.0× 53 0.8× 25 0.4× 12 435
Yong-Min Ju South Korea 5 455 0.9× 90 0.8× 95 1.0× 55 0.9× 25 0.4× 10 511
Boyoung Seo South Korea 3 362 0.7× 90 0.8× 97 1.0× 57 0.9× 25 0.4× 4 418
Xiaoyong Xue China 15 587 1.2× 80 0.7× 51 0.5× 154 2.4× 123 2.0× 86 716
Chorng-Jung Lin Taiwan 8 766 1.5× 99 0.9× 43 0.4× 45 0.7× 78 1.3× 9 804
Yoon-Jong Song South Korea 9 499 1.0× 93 0.8× 113 1.2× 180 2.9× 56 0.9× 13 588
Qilin Zheng China 9 316 0.6× 96 0.8× 49 0.5× 24 0.4× 30 0.5× 41 437

Countries citing papers authored by Soonwan Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Soonwan Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Soonwan Kwon

This figure shows the co-authorship network connecting the top 25 collaborators of Soonwan Kwon. A scholar is included among the top collaborators of Soonwan 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 Soonwan Kwon. Soonwan Kwon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
2.
Song, Jiho, Wooseok Yi, Soonwan Kwon, et al.. (2025). A scalable neural network emulator with MRAM-based mixed-signal circuits. Frontiers in Neuroscience. 19. 1599144–1599144.
3.
Lee, Jaehyuk, et al.. (2025). 5-nm High-Efficiency and High-Density Digital SRAM In-Memory-Computing Macros for AI Accelerators. IEEE Solid-State Circuits Letters. 8. 269–272. 1 indexed citations
4.
Meng, Jian, Dewei Wang, Soonwan Kwon, et al.. (2023). MACC-SRAM: A Multistep Accumulation Capacitor-Coupling In-Memory Computing SRAM Macro for Deep Convolutional Neural Networks. IEEE Journal of Solid-State Circuits. 59(6). 1938–1949. 11 indexed citations
7.
Jung, Seungchul, Hyungwoo Lee, Sungmeen Myung, et al.. (2022). A crossbar array of magnetoresistive memory devices for in-memory computing. Nature. 601(7892). 211–216. 404 indexed citations breakdown →
8.
Yin, Shihui, Minkyu Kim, Soonwan Kwon, et al.. (2022). PIMCA: A Programmable In-Memory Computing Accelerator for Energy-Efficient DNN Inference. IEEE Journal of Solid-State Circuits. 58(5). 1436–1449. 37 indexed citations
9.
Yin, Shihui, Minkyu Kim, Soonwan Kwon, et al.. (2021). PIMCA: A 3.4-Mb Programmable In-Memory Computing Accelerator in 28nm for On-Chip DNN Inference. 1–2. 28 indexed citations
11.
Han, Yong-Woon, et al.. (2009). The SRAM Soft Failure Analysis with SNM & TR Characterization by Nanoprobing in Sub 45nm. Proceedings - International Symposium for Testing and Failure Analysis. 30088. 76–80. 2 indexed citations
12.
Manshina, Alina, Alexey V. Povolotskiy, А. В. Курочкин, et al.. (2007). Laser-induced copper deposition on the surface of an oxide glass from an electrolyte solution. Glass Physics and Chemistry. 33(3). 209–213. 15 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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