Daniel Ashlock

4.0k citations
249 papers · 3.1k · h-index 26

Impact in

Papers in

    • Evolutionary Algorithms and Applications 86
    • Metaheuristic Optimization Algorithms Research 53
    • Artificial Intelligence in Games 30
    • Genomics and Phylogenetic Studies 23

Daniel Ashlock

231 papers receiving 3.0k citations

Peers

Daniel Ashlock
Comparison fields: 5 of 149
  • Artificial Intelligence 1.1k
  • Modeling and Simulation 107
  • Genetics 590
  • Computer Graphics and Computer-Aided Design 81
  • Plant Science 699
Replace Tijl De Bie with:
Tijl De Bie Belgium
Liviu Panait United States
Yue Lu China
Avi Pfeffer United States
Vito Trianni Italy
Chee Seng Chan Malaysia
Jin Ming Koh Singapore
Weng‐Keen Wong United States
Heiko Hamann Germany
Zhiming Zheng China
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Ashlock

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Ashlock

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Ashlock. 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 Daniel Ashlock. The network helps show where Daniel Ashlock may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 249 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006308
2 2004258
3 2002102
4 200676
5 201175
6 200670
7 200663
8 200556
9 200655
10 200854
11 201852
12 200951
13 200442
14 200942
15 200540
16 201039
17 200637
18 200334
19 200334
20 201932

About Daniel Ashlock

Daniel Ashlock is a scholar working on Artificial Intelligence, Molecular Biology, Sociology and Political Science, Genetics and Computational Theory and Mathematics, having authored 249 papers that have together received 3.1k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (86 papers), Metaheuristic Optimization Algorithms Research (53 papers), Evolutionary Game Theory and Cooperation (50 papers), Evolution and Genetic Dynamics (44 papers), Artificial Intelligence in Games (30 papers), Advanced Multi-Objective Optimization Algorithms (25 papers), Genomics and Phylogenetic Studies (23 papers) and Complex Network Analysis Techniques (16 papers). The work is most often cited by research in Artificial Intelligence (1.1k citations), Modeling and Simulation (107 citations), Genetics (590 citations), Computer Graphics and Computer-Aided Design (81 citations) and Plant Science (699 citations). Daniel Ashlock has collaborated with scholars based in Canada, United States and South Korea. Frequent co-authors include Wendy Ashlock, Kenneth M. Bryden, Sheridan Houghten, Patrick S. Schnable, Colin Lee, Justin Schonfeld, Tsui‐Jung Wen, Roger P. Wise, Yan Fu and Ling Guo. Their work appears in journals such as IEEE Transactions on Evolutionary Computation, Biosystems, IEEE Transactions on Computational Intelligence and AI in Games, Genetics and BMC Bioinformatics.

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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