Moises Sudit

18 papers receiving 240 citations

Peers

Moises Sudit
Comparison fields: 5 of 57
  • Computer Networks and Communications 112
  • Information Systems 78
  • Industrial and Manufacturing Engineering 61
  • Artificial Intelligence 58
  • Signal Processing 41
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Citations per year

Countries citing papers authored by Moises Sudit

Since Specialization
Citations

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

Fields of papers citing papers by Moises Sudit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Moises Sudit

This figure shows the co-authorship network connecting the top 25 collaborators of Moises Sudit. A scholar is included among the top collaborators of Moises Sudit 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 Moises Sudit. Moises Sudit is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
#WorkIndexed citations
1 14
2
RDF versus attributed graphs: The war for the best graph representation
4
3
Approximate SPARQL for error tolerant queries on the DBpedia knowledge base
1
4
A multi-perspective optimization approach to UAV resource management for littoral surveillance
8
5 3
6
Progress in Material Handling Research 2012
52
7 0
8 6
9
The role of information fusion in providing analytical rigor for intelligence analysis
2
10
Decentralized cooperative urban tracking of multiple ground targets by a team of autonomous UAVs
8
11 22
12 5
13 48
14
Symbolic Reasoning in the Cyber Security Domain
3
15 23
16 19
17 26
18 2
19
Paroids: A generic environment for local search
2

About Moises Sudit

Moises Sudit is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 19 papers that have together received 248 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (4 papers), Distributed Control Multi-Agent Systems (3 papers) and Information and Cyber Security (3 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (61 citations), Computer Networks and Communications (112 citations) and Signal Processing (41 citations). Moises Sudit has collaborated with scholars based in United States. Frequent co-authors include Michael E. Kuhl, Shanchieh Jay Yang, Rakesh Nagi, Carol J. Romanowski, Andres L. Carrano, Kevin R. Gue, René de Koster, Benoît Montreuil, Daniel Liu and Shambhu Upadhyaya. Their work appears in journals such as IEEE Communications Magazine, IEEE Transactions on Neural Networks and Learning Systems and Computers & Operations Research.

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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