Fabrice Paillet

26 total papers · 1.3k total citations
21 papers, 1.0k citations indexed

About

Fabrice Paillet is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Fabrice Paillet has authored 21 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Electrical and Electronic Engineering, 6 papers in Biomedical Engineering and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Fabrice Paillet's work include Low-power high-performance VLSI design (9 papers), Analog and Mixed-Signal Circuit Design (6 papers) and Semiconductor materials and devices (6 papers). Fabrice Paillet is often cited by papers focused on Low-power high-performance VLSI design (9 papers), Analog and Mixed-Signal Circuit Design (6 papers) and Semiconductor materials and devices (6 papers). Fabrice Paillet collaborates with scholars based in United States, France and Canada. Fabrice Paillet's co-authors include G. Schrom, Donald S. Gardner, Tanay Karnik, Shekhar Borkar, P. Hazucha, Kaladhar Radhakrishnan, Michael J. Hill, Jonathan Douglas, Brice Jamieson and William J. Lambert and has published in prestigious journals such as Journal of Applied Physics, IEEE Journal of Solid-State Circuits and IEEE Transactions on Magnetics.

In The Last Decade

Fabrice Paillet

21 papers receiving 962 citations

Author Peers

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

Author						Papers	Cites
Fabrice Paillet	833	200	144	130	99	21	1.0k
Yi-Chun Shih	1.0k 1.2×	171 0.9×	48 0.3×	245 1.9×	143 1.4×	33	1.2k
Noboru Sakimura	825 1.0×	116 0.6×	64 0.4×	380 2.9×	119 1.2×	40	934
S.E. Steen	825 1.0×	151 0.8×	68 0.5×	162 1.2×	73 0.7×	30	920
Kaladhar Radhakrishnan	903 1.1×	123 0.6×	43 0.3×	36 0.3×	100 1.0×	61	1.0k
Yahya Lakys	712 0.9×	182 0.9×	58 0.4×	349 2.7×	58 0.6×	27	832
Tadahiko Sugibayashi	917 1.1×	52 0.3×	92 0.6×	436 3.4×	152 1.5×	82	1.1k
Dinesh Pamunuwa	854 1.0×	110 0.6×	37 0.3×	109 0.8×	181 1.8×	68	941
Yinxi Jin	940 1.1×	103 0.5×	155 1.1×	179 1.4×	20 0.2×	74	1.2k
Ritwik Chatterjee	905 1.1×	107 0.5×	85 0.6×	50 0.4×	44 0.4×	31	948
Xiaosen Liu	939 1.1×	231 1.2×	61 0.4×	24 0.2×	59 0.6×	72	1.1k

Countries citing papers authored by Fabrice Paillet

Since Specialization

Citations

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

Fields of papers citing papers by Fabrice Paillet

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fabrice Paillet

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