A. Williams
Impact in
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- Distributed Control Multi-Agent Systems
- Neural Networks Stability and Synchronization
- Nonlinear Dynamics and Pattern Formation
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- Adaptive Control of Nonlinear Systems
Papers in
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- Distributed Control Multi-Agent Systems 6
- Neural Networks Stability and Synchronization 3
- Mobile Ad Hoc Networks 1
- Nonlinear Dynamics and Pattern Formation 1
- Opportunistic and Delay-Tolerant Networks 1
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- Control and Dynamics of Mobile Robots 1
- Traffic control and management 1
- Co-authors
- Gerardo Lafferriere (4 shared papers)John S. Caughman (3 shared papers)J. J. P. Veerman (3 shared papers)Sonja Glavaški (2 shared papers)Tarıq Samad (1 shared paper)Madalena Chaves (1 shared paper)Partha P. Nag (1 shared paper)
- Journals
- Journal of Statistical Physics (1 paper)Systems & Control Letters (1 paper)PDXScholar (Portland State University) (1 paper)
- Partner nations
- United States
In The Last Decade
A. Williams
6 papers receiving 633 citations
A. Williams's Hit Papers
Peers
Comparison fields: 5 of 44
- Computer Networks and Communications 626
- Control and Systems Engineering 226
- Aerospace Engineering 103
- Public Health, Environmental and Occupational Health 102
- Computer Vision and Pattern Recognition 54
Countries citing papers authored by A. Williams
This map shows the geographic impact of A. Williams'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 A. Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Williams more than expected).
Fields of papers citing papers by A. Williams
This network shows the impact of papers produced by A. Williams. 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 A. Williams. The network helps show where A. Williams may publish in the future.
Co-authors
The 7 scholars most cited alongside A. Williams, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Decentralized control of vehicle formations Hit paper breakdown → | 2005 | 501 |
| 2 | 2004 | 52 | |
| 3 | 2004 | 42 | |
| 4 | 2005 | 38 | |
| 5 | 2004 | 22 | |
| 6 | 2006 | 16 |
About A. Williams
A. Williams is a scholar working on Computer Networks and Communications, Control and Systems Engineering, Public Health, Environmental and Occupational Health, Aerospace Engineering and Biomedical Engineering, having authored 6 papers that have together received 671 indexed citations. Recurring topics across this work include Distributed Control Multi-Agent Systems (6 papers), Neural Networks Stability and Synchronization (3 papers), Mathematical and Theoretical Epidemiology and Ecology Models (2 papers), Control and Dynamics of Mobile Robots (1 paper), Mobile Ad Hoc Networks (1 paper), Nonlinear Dynamics and Pattern Formation (1 paper), Traffic control and management (1 paper) and Opportunistic and Delay-Tolerant Networks (1 paper). The work is most often cited by research in Computer Networks and Communications (626 citations), Control and Systems Engineering (226 citations), Aerospace Engineering (103 citations), Public Health, Environmental and Occupational Health (102 citations) and Computer Vision and Pattern Recognition (54 citations). A. Williams has collaborated with scholars based in United States. Frequent co-authors include Gerardo Lafferriere, John S. Caughman, J. J. P. Veerman, Sonja Glavaški, Tarıq Samad, Madalena Chaves and Partha P. Nag. Their work appears in journals such as Journal of Statistical Physics, Systems & Control Letters and PDXScholar (Portland State University).
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.