M.J. Avedillo

1.2k citations
114 papers · 830 indexed · h-index 14

Impact in

Papers in

    • Advancements in Semiconductor Devices and Circuit Design 52
    • Low-power high-performance VLSI design 43
    • Semiconductor materials and devices 39
    • Advanced Memory and Neural Computing 23
    • Ferroelectric and Negative Capacitance Devices 12
    • Integrated Circuits and Semiconductor Failure Analysis 9

M.J. Avedillo

108 papers receiving 799 citations

Peers

M.J. Avedillo
Comparison fields: 5 of 41
  • Electrical and Electronic Engineering 717
  • Hardware and Architecture 79
  • Computational Theory and Mathematics 133
  • Artificial Intelligence 200
  • Cognitive Neuroscience 64
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Citations per year

Countries citing papers authored by M.J. Avedillo

Since Specialization
Citations

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

Fields of papers citing papers by M.J. Avedillo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.J. Avedillo. 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 M.J. Avedillo. The network helps show where M.J. Avedillo may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 114 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003172
2 200343
3 202136
4 199535
5 202428
6 202127
7 202124
8 200123
9 200618
10 200418
11 200715
12 201615
13 199415
14 200614
15 200512
16 201710
17 201610
18 200810
19 200910
20 200910

About M.J. Avedillo

M.J. Avedillo is a scholar working on Hardware and Architecture, Electrical and Electronic Engineering, Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications, having authored 114 papers that have together received 830 indexed citations. Recurring topics across this work include Advancements in Semiconductor Devices and Circuit Design (52 papers), Low-power high-performance VLSI design (43 papers), Semiconductor materials and devices (39 papers), Advanced Memory and Neural Computing (23 papers), Neural Networks and Reservoir Computing (13 papers), Analog and Mixed-Signal Circuit Design (12 papers), Ferroelectric and Negative Capacitance Devices (12 papers) and Integrated Circuits and Semiconductor Failure Analysis (9 papers). The work is most often cited by research in Electrical and Electronic Engineering (717 citations), Hardware and Architecture (79 citations), Computational Theory and Mathematics (133 citations), Artificial Intelligence (200 citations) and Cognitive Neuroscience (64 citations). M.J. Avedillo has collaborated with scholars based in Spain, France and Switzerland. Frequent co-authors include José M. Quintana, J.M. Quintana, Juan Núñez, Valeriu Beiu, A. Rueda, B. Linares-Barranco, Manuel Jiménez, J.L. Huertas, Aida Todri‐Sanial and Siegfried Karg. Their work appears in journals such as Electronics Letters, IEEE Transactions on Nanotechnology, Frontiers in Neuroscience, IEEE Transactions on Electron Devices and IEEE Transactions on Circuits and Systems I Regular Papers.

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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