Valerio Milo

2.2k citations
36 papers · 1.8k · h-index 22

Impact in

Papers in

Valerio Milo

35 papers receiving 1.8k citations

Peers

Valerio Milo
Comparison fields: 5 of 50
  • Cellular and Molecular Neuroscience 765
  • Electrical and Electronic Engineering 1.8k
  • Cognitive Neuroscience 381
  • Polymers and Plastics 193
  • Artificial Intelligence 286
Replace Peng Yan with:
Peng Yan United States
Nirmal Ramaswamy United States
Sukru Burc Eryilmaz United States
Giacomo Pedretti Italy
Daniel Belkin United States
Alessandro Calderoni Italy
S. R. Nandakumar United States
Xiaoyan Liu China
Qingjiang Li China
Zuheng Wu China
Valerio Milo relative to Peng Yan United States Peng Yan's profile →
Citations per field
00.5×10×12.8×
Peng Yan · 1×
Citations per year

Countries citing papers authored by Valerio Milo

Since Specialization
Citations

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

Fields of papers citing papers by Valerio Milo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018227
2 2016202
3 2016198
4 2019169
5 2017144
6 2016108
7 2020105
8 202175
9 201766
10 201657
11 201744
12 201840
13 201738
14 201835
15 202234
16 201633
17 201833
18 202032
19 202125
20 201623

About Valerio Milo

Valerio Milo is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience, Cognitive Neuroscience, Artificial Intelligence and Polymers and Plastics, having authored 36 papers that have together received 1.8k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (36 papers), Ferroelectric and Negative Capacitance Devices (22 papers), Photoreceptor and optogenetics research (9 papers), Neural dynamics and brain function (8 papers), Semiconductor materials and devices (7 papers), CCD and CMOS Imaging Sensors (6 papers), Neuroscience and Neural Engineering (4 papers) and Transition Metal Oxide Nanomaterials (3 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (765 citations), Electrical and Electronic Engineering (1.8k citations), Cognitive Neuroscience (381 citations), Polymers and Plastics (193 citations) and Artificial Intelligence (286 citations). Valerio Milo has collaborated with scholars based in Italy, Germany and United States. Frequent co-authors include Daniele Ielmini, Nirmal Ramaswamy, Alessandro Calderoni, Stefano Ambrogio, Roberto Carboni, Giacomo Pedretti, Alessandro S. Spinelli, Zhongqiang Wang, Simone Balatti and Wei Wang. Their work appears in journals such as IEEE Transactions on Electron Devices, Advanced Theory and Simulations, Journal of Computational Electronics, IEEE Transactions on Very Large Scale Integration (VLSI) Systems and Frontiers in Neuroscience.

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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