Matthew P. Evett
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Information Systems top 10%
- Software top 5%
- Computer Vision and Pattern Recognition
- Co-authors
- James HendlerEdward B. AllenWilliam AndersenLee SpectorAmbuj MahantiDana NauThomas FernandezXiaohong Yuan
- Topics
- Neural Networks and Applications (6 papers)AI-based Problem Solving and Planning (4 papers)Evolutionary Algorithms and Applications (4 papers)
- Journals
- Journal of Pain and Symptom ManagementJournal of Parallel and Distributed ComputingIEEE Expert
- Partner nations
- United States
In The Last Decade
Matthew P. Evett
20 papers receiving 182 citations
Peers
Comparison fields: 5 of 37
- Artificial Intelligence 130
- Computer Networks and Communications 75
- Information Systems 74
- Software 64
- Computer Vision and Pattern Recognition 29
Countries citing papers authored by Matthew P. Evett
This map shows the geographic impact of Matthew P. Evett'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 P. Evett with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew P. Evett more than expected).
Fields of papers citing papers by Matthew P. Evett
This network shows the impact of papers produced by Matthew P. Evett. 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 P. Evett. The network helps show where Matthew P. Evett may publish in the future.
Co-authorship network of co-authors of Matthew P. Evett
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew P. Evett. A scholar is included among the top collaborators of Matthew P. Evett 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 Matthew P. Evett. Matthew P. Evett is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | 0 | |
| 5 | 5 | |
| 6 | Using Genetic Programming to Determine Software Quality | 5 |
| 7 | Numeric Mutation: Improved Search in Genetic Programming | 3 |
| 8 | Numeric Mutation Improves the Discovery of Numeric Constants in Genetic Programming | 8 |
| 9 | GP-based software quality prediction | 50 |
| 10 | A distributed system for genetic programming that dynamically allocates processors | 2 |
| 11 | 32 | |
| 12 | Massively parallel matching of knowledge structures | 17 |
| 13 | 5 | |
| 14 | 27 | |
| 15 | 26 | |
| 16 | Massively parallel support for computationally effective recognition queries | 3 |
| 17 | 5 | |
| 18 | An update of PARKA, a massively parallel knowledge representation system | 1 |
| 19 | Knowledge representation in PARKA | 9 |
| 20 | 1 |
About Matthew P. Evett
Matthew P. Evett is a scholar working on Software, Artificial Intelligence and Computer Networks and Communications, having authored 21 papers that have together received 211 indexed citations. Recurring topics across this work include Neural Networks and Applications (6 papers), AI-based Problem Solving and Planning (4 papers) and Evolutionary Algorithms and Applications (4 papers). The work is most often cited by research in Software (64 citations), Artificial Intelligence (130 citations) and Information Systems (74 citations). Matthew P. Evett has collaborated with scholars based in United States. Frequent co-authors include James Hendler, Edward B. Allen, William Andersen, Lee Spector, Ambuj Mahanti, Dana Nau, Thomas Fernandez, Xiaohong Yuan, Kang Zhao and Taghi M. Khoshgoftaar. Their work appears in journals such as Journal of Pain and Symptom Management, Journal of Parallel and Distributed Computing and IEEE Expert.
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.