Ilaria De Munari

2.6k citations
106 papers · 1.8k indexed · 1 hit paper · h-index 20

Ilaria De Munari

99 papers receiving 1.7k citations

Hit Papers

IoT Wearable Sensor and Deep Learning: An Integrated Appr...3162019202620212023100200300

Peers

Ilaria De Munari
Comparison fields: 5 of 126
  • Computer Vision and Pattern Recognition 396
  • Electrical and Electronic Engineering 809
  • Computer Networks and Communications 297
  • Human-Computer Interaction 68
  • Electronic, Optical and Magnetic Materials 172
Replace Ran Liu with:
Ran Liu China
Wilhelm Stork Germany
Faisal Bashir Pakistan
Ching‐Hsing Luo Taiwan
Joo‐Ho Lee Japan
Diego P. Morales Spain
Jun Zhou China
Salina Abdul Samad Malaysia
Hanjun Jiang China
Jin-Hyung Kim South Korea
Ilaria De Munari relative to Ran Liu China Ran Liu's profile →
Citations per field
00.5×4.5×
Ran Liu · 1×
Citations per year

Countries citing papers authored by Ilaria De Munari

Since Specialization
Citations

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

Fields of papers citing papers by Ilaria De Munari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ilaria De Munari. 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 Ilaria De Munari. The network helps show where Ilaria De Munari may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20250
4 20252
5 20241
6 20245
7 20247
8 20240
9 202021
10 201826
11 201760
12 201723
13 201613
14 20144
15 20141
16 201255
17 20122
18
MuSA: A multisensor wearable device for AAL
20118
19
Home smart home: brain-computer interface control for real smart home environments
20106
20
A Biased Resistor Network Model for Electromigration Phenomena in Metallic Lines
20042

About Ilaria De Munari

Ilaria De Munari is a scholar working on Electronic, Optical and Magnetic Materials, Electrical and Electronic Engineering and Hardware and Architecture, having authored 106 papers that have together received 1.8k indexed citations. Recurring topics across this work include Copper Interconnects and Reliability (26 papers), Electronic Packaging and Soldering Technologies (19 papers), Context-Aware Activity Recognition Systems (16 papers), Semiconductor materials and devices (15 papers), Semiconductor materials and interfaces (12 papers), EEG and Brain-Computer Interfaces (9 papers), IoT-based Smart Home Systems (8 papers) and Energy Harvesting in Wireless Networks (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (396 citations), Electrical and Electronic Engineering (809 citations) and Computer Networks and Communications (297 citations). Ilaria De Munari has collaborated with scholars based in Italy, Greece and Belgium. Frequent co-authors include Valentina Bianchi, Paolo Ciampolini, Monica Mordonini, Marco Bassoli, A. Scorzoni, F. Fantini, Gianfranco Lombardo, Paolo Fornacciari, Guido Matrella and Stefano Cagnoni. Their work appears in journals such as Journal of Applied Physics, Physical Review B and Carbohydrate Polymers.

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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