Brian W. Goldman

806 citations
20 papers · 432 indexed · h-index 9
Topics
Evolutionary Algorithms and Applications (14 papers)Metaheuristic Optimization Algorithms Research (12 papers)Advanced Multi-Objective Optimization Algorithms (8 papers)

In The Last Decade

Brian W. Goldman

19 papers receiving 425 citations

Peers

Brian W. Goldman
Comparison fields: 5 of 58
  • Artificial Intelligence 334
  • Computational Theory and Mathematics 144
  • Molecular Biology 96
  • Aerospace Engineering 44
  • Electrical and Electronic Engineering 44
Replace Pauline C. Haddow with:
Pauline C. Haddow Norway
David Haws United States
S. Gustafson United Kingdom
Jan Paredis Netherlands
Miguel Nicolau Ireland
L. B. Soros United States
Felix Streichert Germany
Steven Gustafson United States
Justin K. Pugh United States
Naveen Sivadasan India
Brian W. Goldman relative to Pauline C. Haddow Norway Pauline C. Haddow's profile →
Citations per field
00.5×10×13.3×
Pauline C. Haddow · 1×
Citations per year

Countries citing papers authored by Brian W. Goldman

Since Specialization
Citations

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

Fields of papers citing papers by Brian W. Goldman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian W. Goldman. 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 Brian W. Goldman. The network helps show where Brian W. Goldman may publish in the future.

Co-authorship network of co-authors of Brian W. Goldman

This figure shows the co-authorship network connecting the top 25 collaborators of Brian W. Goldman. A scholar is included among the top collaborators of Brian W. Goldman 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 Brian W. Goldman. Brian W. Goldman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 59
2 7
3 1
4 7
5 6
6 31
7 20
8 4
9 18
10 38
11 56
12 4
13 19
14
Better GP benchmarks: community survey results and proposals
6
15 4
16 125
17 7
18 0
19 7
20 13

About Brian W. Goldman

Brian W. Goldman is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Discrete Mathematics and Combinatorics, having authored 20 papers that have together received 432 indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (14 papers), Metaheuristic Optimization Algorithms Research (12 papers) and Advanced Multi-Objective Optimization Algorithms (8 papers). The work is most often cited by research in Artificial Intelligence (334 citations), Computational Theory and Mathematics (144 citations) and Industrial and Manufacturing Engineering (19 citations). Brian W. Goldman has collaborated with scholars based in United States, United Kingdom and Austria. Frequent co-authors include William F. Punch, Daniel R. Tauritz, Una-May O’Reilly, David R. White, James McDermott, Mauro Castelli, Sean Luke, Gabriel Kronberger, Luca Manzoni and Wojciech Jaśkowski. Their work appears in journals such as PLoS ONE, Expert Systems with Applications and Renewable Energy.

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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