Bernardo Camajori Tedeschini

531 citations
20 papers · 280 · h-index 9

Impact in

    • Privacy-Preserving Technologies in Data
    • Cryptography and Data Security
    • Stochastic Gradient Optimization Techniques
    • Target Tracking and Data Fusion in Sensor Networks

Papers in

    • Indoor and Outdoor Localization Technologies 10
    • Millimeter-Wave Propagation and Modeling 3
    • Vehicular Ad Hoc Networks (VANETs) 2
    • Privacy-Preserving Technologies in Data 5
    • Stochastic Gradient Optimization Techniques 3
    • Target Tracking and Data Fusion in Sensor Networks 3

Bernardo Camajori Tedeschini

17 papers receiving 273 citations

Peers

Bernardo Camajori Tedeschini
Comparison fields: 5 of 54
  • Health Informatics 13
  • Artificial Intelligence 104
  • Computer Networks and Communications 49
  • Neurology 16
  • Signal Processing 22
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Citations per field
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Citations per year

Countries citing papers authored by Bernardo Camajori Tedeschini

Since Specialization
Citations

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

Fields of papers citing papers by Bernardo Camajori Tedeschini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bernardo Camajori Tedeschini. 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 Bernardo Camajori Tedeschini. The network helps show where Bernardo Camajori Tedeschini may publish in the future.

Co-authors

The 18 scholars most cited alongside Bernardo Camajori Tedeschini, 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 Bernardo Camajori Tedeschini Line = papers co-authored together Bernardo Camajori Tedeschini links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
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3 202320
4 202317
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9 20239
10 20228
11 20248
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16 20232
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About Bernardo Camajori Tedeschini

Bernardo Camajori Tedeschini is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Computer Networks and Communications, Signal Processing and Aerospace Engineering, having authored 20 papers that have together received 280 indexed citations. Recurring topics across this work include Indoor and Outdoor Localization Technologies (10 papers), Privacy-Preserving Technologies in Data (5 papers), Stochastic Gradient Optimization Techniques (3 papers), Millimeter-Wave Propagation and Modeling (3 papers), Target Tracking and Data Fusion in Sensor Networks (3 papers), Speech and Audio Processing (3 papers), Vehicular Ad Hoc Networks (VANETs) (2 papers) and Distributed Sensor Networks and Detection Algorithms (2 papers). The work is most often cited by research in Health Informatics (13 citations), Artificial Intelligence (104 citations), Computer Networks and Communications (49 citations), Neurology (16 citations) and Signal Processing (22 citations). Bernardo Camajori Tedeschini has collaborated with scholars based in Italy, United States and Netherlands. Frequent co-authors include Monica Nicoli, Luca Barbieri, Mattia Brambilla, Stefano Savazzi, Luigi Serio, Ioannis Stathopoulos, Moe Z. Win, Huiping Huang, Henk Wymeersch and Máximo Cobos. Their work appears in journals such as IEEE Journal on Selected Areas in Communications, IEEE Access, IEEE Communications Surveys & Tutorials, IEEE Communications Letters and IEEE Transactions on Vehicular Technology.

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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