Moises Sudit

424 citations
19 papers · 248 · h-index 9

Impact in

Papers in

Moises Sudit

18 papers receiving 240 citations

Peers

Moises Sudit
Comparison fields: 5 of 57
  • Industrial and Manufacturing Engineering 61
  • Computer Networks and Communications 112
  • Signal Processing 41
  • Information Systems 78
  • Artificial Intelligence 58
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Emil J. Khatib Spain
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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-authors

The 17 scholars most cited alongside Moises Sudit, 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 Moises Sudit Line = papers co-authored together Moises Sudit links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1
Progress in Material Handling Research 2012
201352
2 200748
3 200526
4 200623
5 201022
6 200619
7 202214
8
Decentralized cooperative urban tracking of multiple ground targets by a team of autonomous UAVs
20118
9
A multi-perspective optimization approach to UAV resource management for littoral surveillance
20138
10 20126
11 20095
12
RDF versus attributed graphs: The war for the best graph representation
20154
13 20133
14
Symbolic Reasoning in the Cyber Security Domain
20073
15
The role of information fusion in providing analytical rigor for intelligence analysis
20112
16 20042
17
Paroids: A generic environment for local search
19882
18
Approximate SPARQL for error tolerant queries on the DBpedia knowledge base
20131
19 20120

About Moises Sudit

Moises Sudit is a scholar working on Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems and Aerospace Engineering, 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), Semantic Web and Ontologies (3 papers), Information and Cyber Security (3 papers), Anomaly Detection Techniques and Applications (3 papers), Human-Automation Interaction and Safety (2 papers), Advanced Graph Neural Networks (2 papers) and Robotic Path Planning Algorithms (2 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (61 citations), Computer Networks and Communications (112 citations), Signal Processing (41 citations), Information Systems (78 citations) and Artificial Intelligence (58 citations). Moises Sudit has collaborated with scholars based in United States. Frequent co-authors include Shanchieh Jay Yang, Michael E. Kuhl, Rakesh Nagi, Carol J. Romanowski, Kevin R. Gue, René de Koster, Andres L. Carrano, Benoît Montreuil, Shambhu Upadhyaya and Katie McConky. Their work appears in journals such as Computers & Operations Research, IEEE Communications Magazine, IEEE Transactions on Neural Networks and Learning Systems, International Conference on Information Fusion and Purdue e-Pubs (Purdue University System).

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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