Hyeonhee Roh

483 citations
30 papers · 405 indexed · h-index 11
Topics
Neuroscience and Neural Engineering (14 papers)Advanced Memory and Neural Computing (13 papers)Advanced Sensor and Energy Harvesting Materials (12 papers)

In The Last Decade

Hyeonhee Roh

28 papers receiving 398 citations

Peers

Hyeonhee Roh
Comparison fields: 5 of 58
  • Biomedical Engineering 282
  • Polymers and Plastics 168
  • Electrical and Electronic Engineering 109
  • Cognitive Neuroscience 88
  • Mechanical Engineering 88
Replace Yoonsoo Shin with:
Yoonsoo Shin South Korea
Rogelio Nuñez‐Flores United States
Chanhyuk Lim South Korea
Mohammad Javad Bathaei Türkiye
Yudai Ogawa Japan
Woo‐Jung Shin South Korea
Seung‐Rok Kim South Korea
Juhyun Lee South Korea
D. Neelima Patnaik India
Yasamin Ziai Poland
Hyeonhee Roh relative to Yoonsoo Shin South Korea Yoonsoo Shin's profile →
Citations per field
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Yoonsoo Shin · 1×
Citations per year

Countries citing papers authored by Hyeonhee Roh

Since Specialization
Citations

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

Fields of papers citing papers by Hyeonhee Roh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hyeonhee Roh

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

All Works

20 of 20 papers shown
#WorkIndexed citations
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Neural information of artificial vision varies depending on the level of spiking heterogeneity across retinal ganglion cells
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About Hyeonhee Roh

Hyeonhee Roh is a scholar working on Cellular and Molecular Neuroscience, Polymers and Plastics and Cognitive Neuroscience, having authored 30 papers that have together received 405 indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (14 papers), Advanced Memory and Neural Computing (13 papers) and Advanced Sensor and Energy Harvesting Materials (12 papers). The work is most often cited by research in Polymers and Plastics (168 citations), Pharmaceutical Science (44 citations) and Biomedical Engineering (282 citations). Hyeonhee Roh has collaborated with scholars based in South Korea, Japan and United States. Frequent co-authors include Daewon Kim, Inkyum Kim, Maesoon Im, Nagabandi Jayababu, Byung Chul Lee, Dong-Hyun Kang, Young Jun Yoon, Seung Min Kwak, Tae Sik Goh and Seungju Jo. Their work appears in journals such as Advanced Functional Materials, Scientific Reports and ACS Applied Materials & Interfaces.

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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