Wooseok Yi

768 total citations · 1 hit paper
16 papers, 542 citations indexed

About

Wooseok Yi is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Wooseok Yi has authored 16 papers receiving a total of 542 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Electrical and Electronic Engineering, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Artificial Intelligence. Recurrent topics in Wooseok Yi's work include Advanced Memory and Neural Computing (9 papers), Ferroelectric and Negative Capacitance Devices (7 papers) and Advanced Neural Network Applications (5 papers). Wooseok Yi is often cited by papers focused on Advanced Memory and Neural Computing (9 papers), Ferroelectric and Negative Capacitance Devices (7 papers) and Advanced Neural Network Applications (5 papers). Wooseok Yi collaborates with scholars based in South Korea, Belgium and United States. Wooseok Yi's co-authors include Jae‐Joon Kim, Shin-Hee Han, Sungmeen Myung, Hyungwoo Lee, Yong-Min Ju, Hyunsoo Kim, Seung Keun Yoon, 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 IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Wooseok Yi

13 papers receiving 530 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A crossbar array of magnetoresistive memory devices for in-memory computing

2022 404 citations Seungchul Jung, Hyungwoo Lee et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Wooseok Yi South Korea	8	429	141	96	77	54	16	542
Soonwan Kwon South Korea	7	495 1.2×	114 0.8×	97 1.0×	26 0.3×	63 1.2×	12	570
Sungmeen Myung South Korea	6	463 1.1×	106 0.8×	94 1.0×	25 0.3×	54 1.0×	9	526
Amogh Agrawal United States	15	673 1.6×	136 1.0×	54 0.6×	53 0.7×	25 0.5×	32	774
Je-Min Hung Taiwan	12	744 1.7×	138 1.0×	41 0.4×	71 0.9×	42 0.8×	15	815
Indranil Chakraborty United States	15	680 1.6×	202 1.4×	52 0.5×	75 1.0×	73 1.4×	36	815
Hui-Yao Kao Taiwan	7	515 1.2×	88 0.6×	32 0.3×	52 0.7×	26 0.5×	7	552
Chorng-Jung Lin Taiwan	8	766 1.8×	99 0.7×	43 0.4×	51 0.7×	45 0.8×	9	804
Qilin Zheng China	9	316 0.7×	96 0.7×	49 0.5×	48 0.6×	24 0.4×	41	437
Christophe Piveteau Switzerland	10	476 1.1×	250 1.8×	75 0.8×	37 0.5×	133 2.5×	20	633
Sheng-Po Huang Taiwan	7	579 1.3×	100 0.7×	21 0.2×	69 0.9×	32 0.6×	10	631

Countries citing papers authored by Wooseok Yi

Since Specialization

Citations

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

Fields of papers citing papers by Wooseok Yi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wooseok Yi

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

All Works

Sort: Min cites: Since: Top N: Style:

16 of 16 papers shown

1.

Kwon, Soonwan, Sungmeen Myung, Hyunsoo Kim, et al.. (2025). 37.3 Monolithic in-Memory Computing Microprocessor for End-to-End DNN Inferencing in MRAM-Embedded 28nm CMOS Technology with 1.1Mb Weight Storage. 1–3.

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.

Myung, Sungmeen, Minje Kim, Wooseok Yi, et al.. (2024). A 14 nm MRAM-Based Multi-bit Analog In-Memory Computing With Process-Variation Calibration for 72 Macros-Based Accelerator. IEEE Solid-State Circuits Letters. 7. 295–298.

4.

Kim, Hyungjun, et al.. (2022). BitBlade: Energy-Efficient Variable Bit-Precision Hardware Accelerator for Quantized Neural Networks. IEEE Journal of Solid-State Circuits. 57(6). 1924–1935. 35 indexed citations

5.

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 →

6.

Choi, Jin‐Young, Dong-Won Kim, Jichan J. Kim, et al.. (2021). Perpendicular-spin-transfer-torque magnetic-tunnel-junction neuron for spiking neural networks depending on the nanoscale grain size of the MgO tunnelling barrier. Materials Advances. 3(3). 1587–1593. 2 indexed citations

7.

Kim, Hyungjun, et al.. (2020). A 44.1TOPS/W Precision-Scalable Accelerator for Quantized Neural Networks in 28nm CMOS. 1–4. 9 indexed citations

8.

Yi, Wooseok, et al.. (2019). Balancing Computation Loads and Optimizing Input Vector Loading in LSTM Accelerators. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 39(9). 1889–1901. 9 indexed citations

9.

Yi, Wooseok, et al.. (2019). GeCo: Classification Restricted Boltzmann Machine Hardware for On-Chip Semisupervised Learning and Bayesian Inference. IEEE Transactions on Neural Networks and Learning Systems. 31(1). 53–65. 7 indexed citations

10.

Kim, Hyungjun, et al.. (2019). BitBlade. 1–6. 40 indexed citations

11.

Yi, Wooseok, Yulhwa Kim, & Jae‐Joon Kim. (2019). Effect of Device Variation on Mapping Binary Neural Network to Memristor Crossbar Array. 320–323. 10 indexed citations

12.

Kung, Jaeha, et al.. (2018). Maximizing system performance by balancing computation loads in LSTM accelerators. 7–12. 17 indexed citations

13.

Yi, Wooseok, et al.. (2017). GeCo. 30–35. 2 indexed citations

14.

Hong, Young Joon, et al.. (2006). Emission spectroscopic diagnostics of argon arc Plasma in Plasma focus device for advanced lithography light source. 15(6). 581–586. 2 indexed citations

15.

Hong, Young Joon, et al.. (2006). Fabrication of the Plasma Focus Device for Advanced Lithography Light Source and Its Electro Optical Characteristics in Argon Arc Plasma. 15(4). 380–386. 2 indexed citations

16.

Jung, Eun‐Young, et al.. (2004). 30.3: Discharge Characteristics of High Efficiency Rib and its Optimized Electrodes (HERO) using High Xe Gas Mixture. SID Symposium Digest of Technical Papers. 35(1). 1030–1033. 3 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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