Marco Vacca

1.3k citations
76 papers · 829 indexed · h-index 17

Marco Vacca

72 papers receiving 810 citations

Peers

Marco Vacca
Comparison fields: 5 of 45
  • Computational Theory and Mathematics 478
  • Electrical and Electronic Engineering 654
  • Atomic and Molecular Physics, and Optics 267
  • Hardware and Architecture 51
  • Biomedical Engineering 141
Replace Mariagrazia Graziano with:
Mariagrazia Graziano Italy
J.E. Brewer United States
Saeed Rasouli Heikalabad Iran
Mark E. Lasher United States
A. Bellaouar United States
J.H. Sinsky United States
Harish M. Kittur India
Manoj Kumar India
Andrea Gerosa Italy
R. K. Sarin India
Marco Vacca relative to Mariagrazia Graziano Italy Mariagrazia Graziano's profile →
Citations per field
00.5×1.5×
Mariagrazia Graziano · 1×
Citations per year

Countries citing papers authored by Marco Vacca

Since Specialization
Citations

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

Fields of papers citing papers by Marco Vacca

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20232
4 20234
5 202214
6 20223
7 20221
8 20213
9 20212
10 20203
11 20209
12 20182
13 201811
14 201729
15 201745
16 20168
17 201619
18 201210
19 19950
20 19905

About Marco Vacca

Marco Vacca is a scholar working on Computational Theory and Mathematics, Electrical and Electronic Engineering and Hardware and Architecture, having authored 76 papers that have together received 829 indexed citations. Recurring topics across this work include Quantum-Dot Cellular Automata (32 papers), Semiconductor materials and devices (28 papers), Advanced Memory and Neural Computing (27 papers), Advancements in Semiconductor Devices and Circuit Design (19 papers), Ferroelectric and Negative Capacitance Devices (17 papers), Quantum and electron transport phenomena (14 papers), Magnetic properties of thin films (10 papers) and Microwave Imaging and Scattering Analysis (8 papers). The work is most often cited by research in Computational Theory and Mathematics (478 citations), Electrical and Electronic Engineering (654 citations) and Atomic and Molecular Physics, and Optics (267 citations). Marco Vacca has collaborated with scholars based in Italy, United Kingdom and United States. Frequent co-authors include Mariagrazia Graziano, Maurizio Zamboni, Giovanna Turvani, Fabrizio Riente, Massimo Ruo Roch, Alessandro Chiolerio, Francesca Vipiana, Mario R. Casu, Azzurra Pulimeno and J. A. Tobón Vasquez. Their work appears in journals such as IEEE Access, Sensors and IEEE Transactions on Electron Devices.

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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