Vincenzo Matta

3.5k citations
114 papers · 1.5k indexed · h-index 21
Topics
Distributed Sensor Networks and Detection Algorithms (66 papers)Target Tracking and Data Fusion in Sensor Networks (49 papers)Distributed Control Multi-Agent Systems (15 papers)

In The Last Decade

Vincenzo Matta

106 papers receiving 1.5k citations

Peers

Vincenzo Matta
Comparison fields: 5 of 72
  • Computer Networks and Communications 1.0k
  • Artificial Intelligence 821
  • Electrical and Electronic Engineering 395
  • Ocean Engineering 155
  • Computational Mechanics 146
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Citations per field
00.5×10×13.8×
Keith Kastella · 1×
Citations per year

Countries citing papers authored by Vincenzo Matta

Since Specialization
Citations

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

Fields of papers citing papers by Vincenzo Matta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vincenzo Matta

This figure shows the co-authorship network connecting the top 25 collaborators of Vincenzo Matta. A scholar is included among the top collaborators of Vincenzo Matta 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 Vincenzo Matta. Vincenzo Matta 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
#WorkIndexed citations
1 1
2 0
3 2
4 3
5 4
6 3
7 21
8 10
9 2
10 17
11 6
12 10
13
Cognitive multistatic AUV networks
19
14
Decentralized nearest-neighbor learning over noisy channels: The uncoded way
2
15
Particle filtering approach to multistatic underwater sensor networks with left-right ambiguity
7
16
Multitarget-multisensor ML and PHD: Some asymptotics
18
17
Predetection Fusion in Large Sensor Networks with Unknown Target Locations.
4
18
Distributed estimation with data association: Is the nearest neighbor the most informative?
1
19
Running consensus in wireless sensor networks
48
20 1

About Vincenzo Matta

Vincenzo Matta is a scholar working on Computer Networks and Communications, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 114 papers that have together received 1.5k indexed citations. Recurring topics across this work include Distributed Sensor Networks and Detection Algorithms (66 papers), Target Tracking and Data Fusion in Sensor Networks (49 papers) and Distributed Control Multi-Agent Systems (15 papers). The work is most often cited by research in Computer Networks and Communications (1.0k citations), Artificial Intelligence (821 citations) and Statistical and Nonlinear Physics (142 citations). Vincenzo Matta has collaborated with scholars based in Italy, United States and Switzerland. Frequent co-authors include Stefano Maranò, Peter Willett, Paolo Braca, Lang Tong, Ali H. Sayed, Mario Di Mauro, P. Addesso, Kevin D. LePage, M. Longo and Dimitri Van De Ville. Their work appears in journals such as IEEE Transactions on Information Theory, Physical Review A and IEEE Transactions on Signal Processing.

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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