Sangheon Oh

711 citations
29 papers · 521 · h-index 10

Impact in

Papers in

Sangheon Oh

25 papers receiving 515 citations

Peers

Sangheon Oh
Comparison fields: 5 of 48
  • Cellular and Molecular Neuroscience 164
  • Electrical and Electronic Engineering 466
  • Polymers and Plastics 88
  • Cognitive Neuroscience 85
  • Artificial Intelligence 108
Replace Jian Kang with:
Jian Kang China
Sijie Ma Hong Kong
Guanrui Wang China
Rashmi Jha United States
S. G. Hu China
Massimo Giordano United States
Yulong Huang China
Seong‐Yun Yun South Korea
Sangheon Oh relative to Jian Kang China Jian Kang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sangheon Oh

Since Specialization
Citations

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

Fields of papers citing papers by Sangheon Oh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sangheon Oh, 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 Sangheon Oh Line = papers co-authored together Sangheon Oh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021121
2 201890
3 202466
4 201942
5 201837
6 202433
7 202030
8 201928
9 202114
10 20199
11 20219
12 20057
13 20216
14 20065
15 20244
16 20253
17 20233
18 20123
19 20233
20 20242

About Sangheon Oh

Sangheon Oh is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Signal Processing, Cellular and Molecular Neuroscience and Cognitive Neuroscience, having authored 29 papers that have together received 521 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (19 papers), Ferroelectric and Negative Capacitance Devices (11 papers), Neural Networks and Reservoir Computing (7 papers), Speech and Audio Processing (4 papers), Machine Learning and ELM (3 papers), Music and Audio Processing (3 papers), Transition Metal Oxide Nanomaterials (2 papers) and Blind Source Separation Techniques (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (164 citations), Electrical and Electronic Engineering (466 citations), Polymers and Plastics (88 citations), Cognitive Neuroscience (85 citations) and Artificial Intelligence (108 citations). Sangheon Oh has collaborated with scholars based in United States, South Korea and Spain. Frequent co-authors include Duygu Kuzum, Yuhan Shi, Xin Liu, Iván K. Schuller, Pavel Salev, Javier del Valle, John R. Jameson, Yi‐Chen Lu, Yoav Kalcheim and Foroozan Koushan. Their work appears in journals such as IEEE Electron Device Letters, Nature Communications, Advanced Materials, IEEE Transactions on Electron Devices and IEEE Transactions on Consumer Electronics.

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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