Gyeong‐Tak Go

1.3k citations
13 papers · 1.1k indexed · 1 hit paper · h-index 10

Gyeong‐Tak Go

13 papers receiving 1.1k citations

Hit Papers

Flexible Neuromorphic Electronics for Computing, Soft Rob...4372019202620212023100200300400

Peers

Gyeong‐Tak Go
Comparison fields: 5 of 44
  • Polymers and Plastics 462
  • Cellular and Molecular Neuroscience 427
  • Electrical and Electronic Engineering 913
  • Biomedical Engineering 293
  • Cognitive Neuroscience 109
Replace Dae‐Gyo Seo with:
Dae‐Gyo Seo South Korea
Xiumei Wang China
Mohit Rameshchandra Kulkarni Singapore
Youhui Chen China
Yang Ming Fu China
Seonghoon Jang South Korea
Changsong Gao China
Rengjian Yu China
Jiangdong Gong China
Huihuang Yang China
Gyeong‐Tak Go relative to Dae‐Gyo Seo South Korea Dae‐Gyo Seo's profile →
Citations per field
00.5×1.5×
Dae‐Gyo Seo · 1×
Citations per year

Countries citing papers authored by Gyeong‐Tak Go

Since Specialization
Citations

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

Fields of papers citing papers by Gyeong‐Tak Go

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gyeong‐Tak Go. 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 Gyeong‐Tak Go. The network helps show where Gyeong‐Tak Go may publish in the future.

Co-authorship network

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

All Works

13 of 13 papers shown
#Work
1 202346
2 202324
3 202315
4 202261
5 202248
6 20221
7 20221
8 202132
9 202089
10
Flexible Neuromorphic Electronics for Computing, Soft Robotics, and Neuroprostheticsbreakdown →
2019437
11 20197
12 2019157
13 2019163

About Gyeong‐Tak Go

Gyeong‐Tak Go is a scholar working on Polymers and Plastics, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering, having authored 13 papers that have together received 1.1k indexed citations. Recurring topics across this work include Conducting polymers and applications (10 papers), Advanced Memory and Neural Computing (9 papers), Neuroscience and Neural Engineering (5 papers), Advanced Sensor and Energy Harvesting Materials (4 papers), Photoreceptor and optogenetics research (3 papers), Perovskite Materials and Applications (2 papers), Organic Electronics and Photovoltaics (1 paper) and Organic Light-Emitting Diodes Research (1 paper). The work is most often cited by research in Polymers and Plastics (462 citations), Cellular and Molecular Neuroscience (427 citations) and Electrical and Electronic Engineering (913 citations). Gyeong‐Tak Go has collaborated with scholars based in South Korea, Sudan and United States. Frequent co-authors include Tae‐Woo Lee, Dae‐Gyo Seo, Yeongjun Lee, Hea‐Lim Park, Wanhee Lee, Hoichang Yang, Mingyuan Pei, Wentao Xu, Hyeon‐Dong Lee and Hobeom Kim. Their work appears in journals such as Advanced Materials, SHILAP Revista de lepidopterología and Advanced Functional Materials.

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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