Can Wu

33 total papers · 753 total citations
23 papers, 283 citations indexed

About

Can Wu is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Can Wu has authored 23 papers receiving a total of 283 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Electrical and Electronic Engineering, 8 papers in Biomedical Engineering and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Can Wu's work include Thin-Film Transistor Technologies (8 papers), Advanced Sensor and Energy Harvesting Materials (7 papers) and Neuroscience and Neural Engineering (3 papers). Can Wu is often cited by papers focused on Thin-Film Transistor Technologies (8 papers), Advanced Sensor and Energy Harvesting Materials (7 papers) and Neuroscience and Neural Engineering (3 papers). Can Wu collaborates with scholars based in United States, China and Germany. Can Wu's co-authors include S. Wagner, M. Lu, G. Gu, Stephen R. Forrest, J. C. Sturm, James C. Sturm, Naveen Verma, Warren Rieutort‐Louis, Liechao Huang and Paul Cuff and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACS Nano and IEEE Journal of Solid-State Circuits.

In The Last Decade

Can Wu

20 papers receiving 273 citations

Author Peers

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

Author						Papers	Cites
Can Wu	221	102	40	35	25	23	283
Zhongqi Ren	134 0.6×	153 1.5×	38 0.9×	63 1.8×	18 0.7×	22	304
Dong Kyun Kim	104 0.5×	179 1.8×	57 1.4×	46 1.3×	13 0.5×	19	281
Kyung-Hwan Kim	265 1.2×	78 0.8×	33 0.8×	43 1.2×	8 0.3×	27	327
Yingzhe Hu	225 1.0×	148 1.5×	11 0.3×	21 0.6×	18 0.7×	25	319
Li Song	216 1.0×	104 1.0×	90 2.3×	84 2.4×	75 3.0×	18	330
Chengjie Du	142 0.6×	110 1.1×	48 1.2×	37 1.1×	24 1.0×	13	273
Saman Azhari	161 0.7×	106 1.0×	32 0.8×	74 2.1×	15 0.6×	31	316
Eunseong Moon	237 1.1×	132 1.3×	24 0.6×	27 0.8×	97 3.9×	19	308
Xusheng Liu	161 0.7×	78 0.8×	40 1.0×	13 0.4×	45 1.8×	30	304
Jonas Groten	88 0.4×	162 1.6×	33 0.8×	84 2.4×	9 0.4×	23	309

Countries citing papers authored by Can Wu

Since Specialization

Citations

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

Fields of papers citing papers by Can Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Can Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Can Wu. A scholar is included among the top collaborators of Can Wu 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 Can Wu. Can Wu 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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