Bernardo Camajori Tedeschini

499 total citations
20 papers, 260 citations indexed

About

Bernardo Camajori Tedeschini is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Bernardo Camajori Tedeschini has authored 20 papers receiving a total of 260 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Electrical and Electronic Engineering, 9 papers in Artificial Intelligence and 4 papers in Computer Networks and Communications. Recurrent topics in Bernardo Camajori Tedeschini's work include Indoor and Outdoor Localization Technologies (10 papers), Privacy-Preserving Technologies in Data (5 papers) and Speech and Audio Processing (3 papers). Bernardo Camajori Tedeschini is often cited by papers focused on Indoor and Outdoor Localization Technologies (10 papers), Privacy-Preserving Technologies in Data (5 papers) and Speech and Audio Processing (3 papers). Bernardo Camajori Tedeschini collaborates with scholars based in Italy, United States and Netherlands. Bernardo Camajori Tedeschini's co-authors include Monica Nicoli, Luca Barbieri, Mattia Brambilla, Stefano Savazzi, Ioannis Stathopoulos, Luigi Serio, Moe Z. Win, Henk Wymeersch, Huiping Huang and Máximo Cobos and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Signal Processing and IEEE Communications Surveys & Tutorials.

In The Last Decade

Bernardo Camajori Tedeschini

17 papers receiving 253 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bernardo Camajori Tedeschini Italy 9 102 101 45 40 20 20 260
Jan Erik Håkegård Norway 8 85 0.8× 84 0.8× 56 1.2× 23 0.6× 4 0.2× 31 276
Bassem Ouni United Arab Emirates 7 75 0.7× 131 1.3× 88 2.0× 41 1.0× 25 1.3× 34 285
Hang Qi China 6 99 1.0× 98 1.0× 49 1.1× 13 0.3× 13 0.7× 16 230
R. Kalidoss India 12 199 2.0× 49 0.5× 100 2.2× 111 2.8× 14 0.7× 30 350
Bakhtiar Ali Pakistan 9 160 1.6× 42 0.4× 116 2.6× 44 1.1× 6 0.3× 32 262
Jian Guo China 10 94 0.9× 77 0.8× 140 3.1× 57 1.4× 15 0.8× 51 279
Kent Gauen United States 5 44 0.4× 96 1.0× 30 0.7× 14 0.3× 21 1.1× 8 235
Gyanendra Kumar India 9 59 0.6× 48 0.5× 95 2.1× 23 0.6× 12 0.6× 35 224
Bilal Saoud Algeria 9 58 0.6× 63 0.6× 62 1.4× 17 0.4× 7 0.3× 32 230
Zhaowei Zhu China 11 59 0.6× 98 1.0× 99 2.2× 11 0.3× 14 0.7× 23 283

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-authorship network of co-authors of Bernardo Camajori Tedeschini

This figure shows the co-authorship network connecting the top 25 collaborators of Bernardo Camajori Tedeschini. A scholar is included among the top collaborators of Bernardo Camajori Tedeschini based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bernardo Camajori Tedeschini. Bernardo Camajori Tedeschini is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Tedeschini, Bernardo Camajori, Stefano Savazzi, & Monica Nicoli. (2025). Weighted Average Consensus Algorithms in Distributed and Federated Learning. IEEE Transactions on Network Science and Engineering. 12(2). 1369–1382. 1 indexed citations
2.
Tedeschini, Bernardo Camajori, et al.. (2024). A Tutorial on 5G Positioning. IEEE Communications Surveys & Tutorials. 27(3). 1488–1535. 28 indexed citations
3.
Barbieri, Luca, et al.. (2024). On the Impact of Data Heterogeneity in Federated Learning Environments with Application to Healthcare Networks. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 1017–1023. 3 indexed citations
4.
Brambilla, Mattia, Bernardo Camajori Tedeschini, Alessandro Fumagalli, et al.. (2024). Integration of 5G and GNSS Technologies for Enhanced Positioning: An Experimental Study. IEEE Open Journal of the Communications Society. 5. 7197–7215. 2 indexed citations
5.
Tedeschini, Bernardo Camajori, et al.. (2024). Pedestrian Positioning in Urban Environments with 5G Technology. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 1–6. 3 indexed citations
6.
Tedeschini, Bernardo Camajori, Girim Kwon, Monica Nicoli, & Moe Z. Win. (2024). Real-Time Bayesian Neural Networks for 6G Cooperative Positioning and Tracking. IEEE Journal on Selected Areas in Communications. 42(9). 2322–2338. 8 indexed citations
7.
Tedeschini, Bernardo Camajori, Mattia Brambilla, & Monica Nicoli. (2024). Split Consensus Federated Learning: An Approach for Distributed Training and Inference. IEEE Access. 12. 119535–119549. 3 indexed citations
8.
Tedeschini, Bernardo Camajori, Mattia Brambilla, Monica Nicoli, & Moe Z. Win. (2024). Multi-Agent Reinforcement Learning for Distributed Cooperative Vehicular Positioning. IEEE Transactions on Intelligent Vehicles. 10(7). 4052–4067. 1 indexed citations
9.
Tedeschini, Bernardo Camajori, Mattia Brambilla, Monica Nicoli, & Moe Z. Win. (2024). Cooperative Positioning with Multi-Agent Reinforcement Learning. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 1–7. 1 indexed citations
10.
Tedeschini, Bernardo Camajori, Girim Kwon, Monica Nicoli, & Moe Z. Win. (2024). Empowering 6G Positioning and Tracking with Bayesian Neural Networks. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 2276–2281.
11.
Roger, Sandra, Mattia Brambilla, Bernardo Camajori Tedeschini, et al.. (2023). Deep-Learning-Based Radio Map Reconstruction for V2X Communications. IEEE Transactions on Vehicular Technology. 73(3). 3863–3871. 16 indexed citations
12.
Tedeschini, Bernardo Camajori, et al.. (2023). A feasibility study of 5G positioning with current cellular network deployment. Scientific Reports. 13(1). 15281–15281. 10 indexed citations
13.
Tedeschini, Bernardo Camajori, Monica Nicoli, & Moe Z. Win. (2023). On the Latent Space of mmWave MIMO Channels for NLOS Identification in 5G-Advanced Systems. IEEE Journal on Selected Areas in Communications. 41(6). 1655–1669. 16 indexed citations
14.
Tedeschini, Bernardo Camajori, Stefano Savazzi, & Monica Nicoli. (2023). A Traffic Model Based Approach to Parameter Server Design in Federated Learning Processes. IEEE Communications Letters. 27(7). 1774–1778. 2 indexed citations
15.
Tedeschini, Bernardo Camajori, Mattia Brambilla, & Monica Nicoli. (2023). Message Passing Neural Network Versus Message Passing Algorithm for Cooperative Positioning. IEEE Transactions on Cognitive Communications and Networking. 9(6). 1666–1676. 12 indexed citations
16.
Tedeschini, Bernardo Camajori & Monica Nicoli. (2023). Cooperative Deep-Learning Positioning in mmWave 5G-Advanced Networks. IEEE Journal on Selected Areas in Communications. 41(12). 3799–3815. 19 indexed citations
17.
Barbieri, Luca, Bernardo Camajori Tedeschini, Mattia Brambilla, & Monica Nicoli. (2023). Implicit Vehicle Positioning with Cooperative Lidar Sensing. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 1–5. 9 indexed citations
18.
Tedeschini, Bernardo Camajori, et al.. (2023). Cooperative Lidar Sensing for Pedestrian Detection: Data Association Based on Message Passing Neural Networks. IEEE Transactions on Signal Processing. 71. 3028–3042. 17 indexed citations
19.
Tedeschini, Bernardo Camajori, Stefano Savazzi, Luca Barbieri, et al.. (2022). Decentralized Federated Learning for Healthcare Networks: A Case Study on Tumor Segmentation. IEEE Access. 10. 8693–8708. 101 indexed citations
20.
Tedeschini, Bernardo Camajori, Mattia Brambilla, Luca Barbieri, & Monica Nicoli. (2022). Addressing data association by message passing over graph neural networks. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 1–7. 8 indexed citations

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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