Grant Dick
Impact in
- Artificial Intelligence top 5%
- Evolutionary Algorithms and Applications
- Metaheuristic Optimization Algorithms Research
- Reinforcement Learning in Robotics
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- Advanced Multi-Objective Optimization Algorithms
Papers in
-
- Metaheuristic Optimization Algorithms Research 33
- Evolutionary Algorithms and Applications 32
- Reinforcement Learning in Robotics 4
- Genetics 16
- Evolution and Genetic Dynamics 15
- Co-authors
- Peter A. Whigham (35 shared papers)James Maclaurin (3 shared papers)Xin Yao (1 shared paper)Friedrich Recknagel (1 shared paper)Hamish G. Spencer (2 shared papers)Yuhui Shi (2 shared papers)Will Neil Browne (2 shared papers)Lam Thu Bui (2 shared papers)
- Journals
- Genetic Programming and Evolvable Machines (4 papers)IEEE Transactions on Evolutionary Computation (4 papers)Lecture notes in computer science (13 papers)Aquaculture (1 paper)Theoretical Population Biology (1 paper)
- Partner nations
- New ZealandAustraliaUnited Kingdom
In The Last Decade
Grant Dick
54 papers receiving 485 citations
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 373
- Computational Theory and Mathematics 93
- Signal Processing 31
- Computer Networks and Communications 57
- Ecological Modeling 9
Countries citing papers authored by Grant Dick
This map shows the geographic impact of Grant Dick'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 Grant Dick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Grant Dick more than expected).
Fields of papers citing papers by Grant Dick
This network shows the impact of papers produced by Grant Dick. 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 Grant Dick. The network helps show where Grant Dick may publish in the future.
Co-authors
The 20 scholars most cited alongside Grant Dick, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 50 | |
| 2 | 2015 | 34 | |
| 3 | 2004 | 28 | |
| 4 | 2014 | 28 | |
| 5 | Feature selection of intrusion detection data using a hybrid genetic algorithm/KNN approach | 2003 | 22 |
| 6 | 2017 | 22 | |
| 7 | 2020 | 21 | |
| 8 | 2017 | 16 | |
| 9 | 2014 | 16 | |
| 10 | 2018 | 15 | |
| 11 | 2010 | 14 | |
| 12 | 2015 | 14 | |
| 13 | 2007 | 14 | |
| 14 | 2014 | 12 | |
| 15 | 2005 | 12 | |
| 16 | 2015 | 11 | |
| 17 | 2022 | 11 | |
| 18 | 2018 | 11 | |
| 19 | 2020 | 10 | |
| 20 | A Comparison of Localised and Global Niching Methods | 2005 | 9 |
About Grant Dick
Grant Dick is a scholar working on Artificial Intelligence, Genetics, Computational Theory and Mathematics, Ecology, Evolution, Behavior and Systematics and Ecological Modeling, having authored 56 papers that have together received 507 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (33 papers), Evolutionary Algorithms and Applications (32 papers), Evolution and Genetic Dynamics (15 papers), Viral Infectious Diseases and Gene Expression in Insects (9 papers), Evolutionary Game Theory and Cooperation (9 papers), Advanced Multi-Objective Optimization Algorithms (7 papers), Reinforcement Learning in Robotics (4 papers) and Animal Behavior and Reproduction (4 papers). The work is most often cited by research in Artificial Intelligence (373 citations), Computational Theory and Mathematics (93 citations), Signal Processing (31 citations), Computer Networks and Communications (57 citations) and Ecological Modeling (9 citations). Grant Dick has collaborated with scholars based in New Zealand, Australia and United Kingdom. Frequent co-authors include Peter A. Whigham, James Maclaurin, Xin Yao, Friedrich Recknagel, Hamish G. Spencer, Yuhui Shi, Will Neil Browne, Lam Thu Bui, Hisao Ishibuchi and Stephen Cranefield. Their work appears in journals such as Genetic Programming and Evolvable Machines, IEEE Transactions on Evolutionary Computation, Lecture notes in computer science, Aquaculture and Theoretical Population Biology.
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.