Stephanie E. Liu

402 citations
14 papers · 303 · h-index 8

Impact in

Papers in

Stephanie E. Liu

14 papers receiving 303 citations

Peers

Stephanie E. Liu
Comparison fields: 5 of 46
  • Cellular and Molecular Neuroscience 78
  • Electrical and Electronic Engineering 226
  • Polymers and Plastics 37
  • Materials Chemistry 98
  • Artificial Intelligence 37
Replace Ruixuan Peng with:
Ruixuan Peng China
Dunan Hu China
Yiwen Ren China
Wenjuan Ci China
Haewon Cho South Korea
Mu‐Pai Lee Taiwan
Kevin C. Matthews United States
Chansoo Yoon South Korea
Tanmay Chavan United States
William A. Gaviria Rojas United States
Stephanie E. Liu relative to Ruixuan Peng China Ruixuan Peng's profile →
Citations per field
00.5×
Ruixuan Peng · 1×
Citations per year

Countries citing papers authored by Stephanie E. Liu

Since Specialization
Citations

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

Fields of papers citing papers by Stephanie E. Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephanie E. Liu. 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 Stephanie E. Liu. The network helps show where Stephanie E. Liu may publish in the future.

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 202369
2 202166
3 202163
4 202325
5 202221
6 202019
7 202311
8 20249
9 20227
10 20245
11 20225
12 20231
13 20231
14 20241

About Stephanie E. Liu

Stephanie E. Liu is a scholar working on Electrical and Electronic Engineering, Materials Chemistry, Biomedical Engineering, Cellular and Molecular Neuroscience and Artificial Intelligence, having authored 14 papers that have together received 303 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (9 papers), Ferroelectric and Negative Capacitance Devices (8 papers), 2D Materials and Applications (5 papers), Neural Networks and Reservoir Computing (2 papers), Neuroscience and Neural Engineering (1 paper), Nanowire Synthesis and Applications (1 paper), Fluorine in Organic Chemistry (1 paper) and Neural dynamics and brain function (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (78 citations), Electrical and Electronic Engineering (226 citations), Polymers and Plastics (37 citations), Materials Chemistry (98 citations) and Artificial Intelligence (37 citations). Stephanie E. Liu has collaborated with scholars based in United States, Japan and South Korea. Frequent co-authors include Mark C. Hersam, Vinod K. Sangwan, Hong‐Sub Lee, Amit Ranjan Trivedi, Xiaodong Yan, Jin‐Gyu Lee, Hyung‐Kyu Lim, Sung‐Eun Kim, Leo Ling and Jiangtan Yuan. Their work appears in journals such as Advanced Materials Technologies, Journal of materials research/Pratt's guide to venture capital sources, Applied Physics Letters, Nature and Nano Letters.

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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