Yang Ming Fu

28 total papers · 1.1k total citations
21 papers, 919 citations indexed

About

Yang Ming Fu is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Polymers and Plastics. According to data from OpenAlex, Yang Ming Fu has authored 21 papers receiving a total of 919 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Electrical and Electronic Engineering, 11 papers in Cellular and Molecular Neuroscience and 5 papers in Polymers and Plastics. Recurrent topics in Yang Ming Fu's work include Advanced Memory and Neural Computing (14 papers), Neuroscience and Neural Engineering (10 papers) and Transition Metal Oxide Nanomaterials (3 papers). Yang Ming Fu is often cited by papers focused on Advanced Memory and Neural Computing (14 papers), Neuroscience and Neural Engineering (10 papers) and Transition Metal Oxide Nanomaterials (3 papers). Yang Ming Fu collaborates with scholars based in China, United Kingdom and Singapore. Yang Ming Fu's co-authors include Li Qiang Zhu, Qing Wan, Liqiang Zhu, Xiaodong Chen, Liang Pan, Ming Wang, Naoji Matsuhisa, Hui Yang, Geng Chen and Changjin Wan and has published in prestigious journals such as Advanced Materials, Nature Communications and Applied Physics Letters.

In The Last Decade

Yang Ming Fu

20 papers receiving 905 citations

Hit Papers

An Artificial Sensory Neu... 2018 2026 2020 2023 2018 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Yang Ming Fu 747 367 263 208 183 21 919
Bongsik Choi 719 1.0× 220 0.6× 447 1.7× 201 1.0× 109 0.6× 35 1.0k
Xiao Qiu 982 1.3× 207 0.6× 304 1.2× 197 0.9× 68 0.4× 24 1.2k
Sanghyeon Choi 1.0k 1.4× 432 1.2× 143 0.5× 270 1.3× 137 0.7× 28 1.1k
Jinsu Yoon 849 1.1× 278 0.8× 473 1.8× 238 1.1× 123 0.7× 42 1.2k
Qingxuan Li 758 1.0× 296 0.8× 113 0.4× 190 0.9× 55 0.3× 50 906
Abhishek A. Sharma 688 0.9× 193 0.5× 103 0.4× 222 1.1× 77 0.4× 46 966
Chunwei Zhang 869 1.2× 226 0.6× 448 1.7× 282 1.4× 137 0.7× 35 1.1k
Sung Woon Cho 892 1.2× 311 0.8× 129 0.5× 203 1.0× 60 0.3× 44 1.0k
Kate J. Norris 880 1.2× 325 0.9× 48 0.2× 208 1.0× 105 0.6× 36 952
Fuyou Liao 883 1.2× 220 0.6× 196 0.7× 126 0.6× 71 0.4× 26 1.1k

Countries citing papers authored by Yang Ming Fu

Since Specialization
Citations

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

Fields of papers citing papers by Yang Ming Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yang Ming Fu. 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 Yang Ming Fu. The network helps show where Yang Ming Fu may publish in the future.

Co-authorship network of co-authors of Yang Ming Fu

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

All Works

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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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