Matthew E. Gaston

616 citations
20 papers · 313 · h-index 8

Impact in

Papers in

Matthew E. Gaston

19 papers receiving 297 citations

Peers

Matthew E. Gaston
Comparison fields: 5 of 73
  • Media Technology 65
  • Computer Science Applications 32
  • Statistical and Nonlinear Physics 58
  • Management Science and Operations Research 44
  • Computer Networks and Communications 69
Replace Kamalika Das with:
Kamalika Das United States
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Citations per year

Countries citing papers authored by Matthew E. Gaston

Since Specialization
Citations

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

Fields of papers citing papers by Matthew E. Gaston

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew E. Gaston. 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 Matthew E. Gaston. The network helps show where Matthew E. Gaston may publish in the future.

Co-authors

The 25 scholars most cited alongside Matthew E. Gaston, 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 Matthew E. Gaston Line = papers co-authored together Matthew E. Gaston links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2019107
2 200588
3 200622
4 200820
5
Using graph diameter for change detection in dynamic networks.
200612
6
Adapting Network Structure for Efficient Team Formation.
200411
7 199910
8 20029
9
Agent-organized networks for multi-agent production and exchange
20057
10
Social Network Structures and Their Impact on Multi-Agent System Dynamics.
20056
11 20214
12
Learning by Demonstration to Support Military Planning and Decision Making
20093
13 20093
14
Organizational learning and network adaptation in multi-agent systems
20053
15 19992
16 20182
17 20042
18 20081
19 20151
20 20120

About Matthew E. Gaston

Matthew E. Gaston is a scholar working on Statistical and Nonlinear Physics, Sociology and Political Science, Information Systems, Computational Mechanics and Artificial Intelligence, having authored 20 papers that have together received 313 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (9 papers), Opinion Dynamics and Social Influence (7 papers), Evolutionary Game Theory and Cooperation (5 papers), Software Engineering Research (3 papers), Aerodynamics and Acoustics in Jet Flows (2 papers), Infection Control and Ventilation (1 paper), Optimization and Packing Problems (1 paper) and Reliability and Maintenance Optimization (1 paper). The work is most often cited by research in Media Technology (65 citations), Computer Science Applications (32 citations), Statistical and Nonlinear Physics (58 citations), Management Science and Operations Research (44 citations) and Computer Networks and Communications (69 citations). Matthew E. Gaston has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Marie desJardins, Bryce Goodman, Nirav Patel, Eric Heim, Howie Choset, Jigar Doshi, Ritwik Gupta, M. Kraetzl, W. D. Wallis and John Simmons. Their work appears in journals such as AI Magazine, Computers & Operations Research, Autonomous Agents and Multi-Agent Systems, Nature Microbiology and Computational Intelligence.

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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