Junsu Yu

502 citations
26 papers · 378 · h-index 13

Impact in

Papers in

Junsu Yu

25 papers receiving 363 citations

Peers

Junsu Yu
Comparison fields: 5 of 21
  • Electrical and Electronic Engineering 363
  • Cellular and Molecular Neuroscience 46
  • Materials Chemistry 71
  • Artificial Intelligence 38
  • Cognitive Neuroscience 22
Replace Sarbashis Das with:
Sarbashis Das United States
Xiaoyan Xu China
Jörg Schreiter Germany
Md. Hasan Raza Ansari Saudi Arabia
Ahish Shylendra United States
Kyung Kyu Min South Korea
Kensuke Ota Japan
Zia Karim United States
Harikrishnan Ravichandran United States
Ryun‐Han Koo South Korea
Junsu Yu relative to Sarbashis Das United States Sarbashis Das's profile →
Citations per field
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Sarbashis Das · 1×
Citations per year

Countries citing papers authored by Junsu Yu

Since Specialization
Citations

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

Fields of papers citing papers by Junsu Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Junsu Yu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Junsu Yu Line = papers co-authored together Junsu Yu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202150
2 202143
3 202033
4 202231
5 202026
6 202324
7 202123
8 202119
9 202118
10 202218
11 202115
12 201913
13 202013
14 202210
15 20209
16 20256
17 20226
18 20215
19 20243
20 20243

About Junsu Yu

Junsu Yu is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Materials Chemistry, Artificial Intelligence and Biomedical Engineering, having authored 26 papers that have together received 378 indexed citations. Recurring topics across this work include Semiconductor materials and devices (16 papers), Ferroelectric and Negative Capacitance Devices (15 papers), Advanced Memory and Neural Computing (14 papers), Advancements in Semiconductor Devices and Circuit Design (5 papers), Advanced Data Storage Technologies (4 papers), MXene and MAX Phase Materials (4 papers), Nanowire Synthesis and Applications (3 papers) and Neural Networks and Reservoir Computing (3 papers). The work is most often cited by research in Electrical and Electronic Engineering (363 citations), Cellular and Molecular Neuroscience (46 citations), Materials Chemistry (71 citations), Artificial Intelligence (38 citations) and Cognitive Neuroscience (22 citations). Junsu Yu has collaborated with scholars based in South Korea and China. Frequent co-authors include Sungmin Hwang, Byung‐Gook Park, Hyungjin Kim, Jong‐Ho Lee, Kyung Kyu Min, Yeonwoo Kim, Min Song, Daewoong Kwon, Sihyun Kim and Jong-Ho Lee. Their work appears in journals such as IEEE Transactions on Electron Devices, IEEE Electron Device Letters, Nanotechnology, Journal of Nanoscience and Nanotechnology and Japanese Journal of Applied Physics.

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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