Daniele Garbin

79 total papers · 1.5k total citations
59 papers, 1.0k citations indexed

About

Daniele Garbin is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Daniele Garbin has authored 59 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Electrical and Electronic Engineering, 38 papers in Materials Chemistry and 8 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Daniele Garbin's work include Advanced Memory and Neural Computing (47 papers), Phase-change materials and chalcogenides (35 papers) and Ferroelectric and Negative Capacitance Devices (15 papers). Daniele Garbin is often cited by papers focused on Advanced Memory and Neural Computing (47 papers), Phase-change materials and chalcogenides (35 papers) and Ferroelectric and Negative Capacitance Devices (15 papers). Daniele Garbin collaborates with scholars based in Belgium, France and United Kingdom. Daniele Garbin's co-authors include Elisa Vianello, L. Perniola, Sergiu Clima, Gouri Sankar Kar, Olivier Bichler, R. Degraeve, B. DeSalvo, Quentin Rafhay, A. Fantini and Christian Gamrat and has published in prestigious journals such as Applied Surface Science, IEEE Transactions on Electron Devices and Thin Solid Films.

In The Last Decade

Daniele Garbin

56 papers receiving 1.0k citations

Author Peers

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

Author						Papers	Cites
Daniele Garbin	960	513	209	169	106	59	1.0k
Jongmyung Yoo	651 0.7×	415 0.8×	189 0.9×	122 0.7×	65 0.6×	39	955
Bhaswar Chakrabarti	967 1.0×	201 0.4×	346 1.7×	108 0.6×	105 1.0×	40	1.0k
Wen Sun	743 0.8×	165 0.3×	261 1.2×	149 0.9×	109 1.0×	63	1.2k
Shaochuan Chen	763 0.8×	235 0.5×	269 1.3×	157 0.9×	58 0.5×	28	852
Kate J. Norris	880 0.9×	199 0.4×	325 1.6×	208 1.2×	105 1.0×	36	952
Xianhu Liang	1.1k 1.1×	425 0.8×	354 1.7×	203 1.2×	58 0.5×	17	1.2k
Sijung Yoo	823 0.9×	405 0.8×	229 1.1×	186 1.1×	57 0.5×	31	927
Kaichen Zhu	787 0.8×	416 0.8×	207 1.0×	100 0.6×	43 0.4×	38	975
Victoria Chen	761 0.8×	520 1.0×	220 1.1×	127 0.8×	42 0.4×	16	1.0k
Damien Deleruyelle	781 0.8×	238 0.5×	155 0.7×	136 0.8×	30 0.3×	66	832

Countries citing papers authored by Daniele Garbin

Since Specialization

Citations

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

Fields of papers citing papers by Daniele Garbin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniele Garbin

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