Thomas Helmuth

1.4k total citations
44 papers, 569 citations indexed

About

Thomas Helmuth is a scholar working on Artificial Intelligence, Molecular Biology and Computer Science Applications. According to data from OpenAlex, Thomas Helmuth has authored 44 papers receiving a total of 569 indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Artificial Intelligence, 20 papers in Molecular Biology and 8 papers in Computer Science Applications. Recurrent topics in Thomas Helmuth's work include Evolutionary Algorithms and Applications (43 papers), Metaheuristic Optimization Algorithms Research (37 papers) and Viral Infectious Diseases and Gene Expression in Insects (10 papers). Thomas Helmuth is often cited by papers focused on Evolutionary Algorithms and Applications (43 papers), Metaheuristic Optimization Algorithms Research (37 papers) and Viral Infectious Diseases and Gene Expression in Insects (10 papers). Thomas Helmuth collaborates with scholars based in United States, Germany and Poland. Thomas Helmuth's co-authors include Lee Spector, Nicholas Freitag McPhee, James Matheson, Peter Kelly, William La Cava, Jason H. Moore, Kyle Harrington, Brian Martin, Krzysztof Krawiec and Paweł Liskowski and has published in prestigious journals such as IEEE Transactions on Evolutionary Computation, Evolutionary Computation and Genetic Programming and Evolvable Machines.

In The Last Decade

Thomas Helmuth

42 papers receiving 547 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Thomas Helmuth United States 13 529 186 85 61 59 44 569
Guy Katz Israel 8 164 0.3× 24 0.1× 9 0.1× 75 1.2× 23 0.4× 23 289
Jennifer Vendetti United States 5 143 0.3× 130 0.7× 7 0.1× 10 0.2× 56 0.9× 8 243
Yuk Wah Wong United States 8 752 1.4× 292 1.6× 4 0.0× 8 0.1× 82 1.4× 11 856
Frank Drewes Sweden 9 205 0.4× 63 0.3× 3 0.0× 9 0.1× 31 0.5× 67 295
Peter Friedland United States 10 144 0.3× 131 0.7× 3 0.0× 24 0.4× 21 0.4× 24 319
Yu-Shi Lin Taiwan 7 148 0.3× 123 0.7× 32 0.4× 10 0.2× 25 0.4× 13 250
S. Gustafson United Kingdom 6 238 0.4× 61 0.3× 3 0.0× 28 0.5× 11 0.2× 8 303
Catherine McCartin New Zealand 11 77 0.1× 27 0.1× 4 0.0× 17 0.3× 87 1.5× 22 238
Carlos R. Rivero United States 10 188 0.4× 40 0.2× 35 0.4× 2 0.0× 146 2.5× 38 283
Hu Ding United States 9 121 0.2× 85 0.5× 111 1.3× 22 0.4× 19 0.3× 35 297

Countries citing papers authored by Thomas Helmuth

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Helmuth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Helmuth

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Helmuth. A scholar is included among the top collaborators of Thomas Helmuth 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 Thomas Helmuth. Thomas Helmuth 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
1.
Briesch, Martin, Dominik Sobania, Alexander Lalejini, et al.. (2024). Informed Down-Sampled Lexicase Selection: Identifying Productive Training Cases for Efficient Problem Solving. Evolutionary Computation. 32(4). 307–337. 2 indexed citations
2.
Briesch, Martin, et al.. (2024). A Comprehensive Analysis of Down-sampling for Genetic Programming-based Program Synthesis. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 487–490.
3.
Briesch, Martin, et al.. (2023). The Problem Solving Benefits of Down-sampling Vary by Selection Scheme. 527–530. 3 indexed citations
4.
Helmuth, Thomas, et al.. (2023). Human-Driven Genetic Programming for Program Synthesis: A Prototype. 1981–1989. 1 indexed citations
5.
Helmuth, Thomas, et al.. (2023). Solving Novel Program Synthesis Problems with Genetic Programming using Parametric Polymorphism. Proceedings of the Genetic and Evolutionary Computation Conference. 3 indexed citations
6.
Helmuth, Thomas & William La Cava. (2022). Lexicase selection. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 1385–1397.
7.
Ding, Li, et al.. (2022). Going faster and hence further with lexicase selection. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 538–541. 2 indexed citations
8.
Helmuth, Thomas. (2021). General Program Synthesis from Examples Using Genetic Programming with Parent Selection Based on Random Lexicographic Orderings of Test Cases. Scholarworks (University of Massachusetts Amherst). 1 indexed citations
9.
Helmuth, Thomas & Peter Kelly. (2021). PSB2. Proceedings of the Genetic and Evolutionary Computation Conference. 785–794. 23 indexed citations
10.
Helmuth, Thomas, et al.. (2020). On the importance of specialists for lexicase selection. Genetic Programming and Evolvable Machines. 21(3). 349–373. 9 indexed citations
11.
Helmuth, Thomas, et al.. (2020). Benchmarking parent selection for program synthesis by genetic programming. 237–238. 15 indexed citations
12.
Helmuth, Thomas, Nicholas Freitag McPhee, & Lee Spector. (2018). Program synthesis using uniform mutation by addition and deletion. Proceedings of the Genetic and Evolutionary Computation Conference. 1127–1134. 30 indexed citations
13.
Helmuth, Thomas, et al.. (2017). On the difficulty of benchmarking inductive program synthesis methods. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 1589–1596. 8 indexed citations
14.
Helmuth, Thomas, et al.. (2017). Improving generalization of evolved programs through automatic simplification. Proceedings of the Genetic and Evolutionary Computation Conference. 937–944. 31 indexed citations
15.
McPhee, Nicholas Freitag, et al.. (2017). Visualizing genetic programming ancestries using graph databases. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 245–246. 3 indexed citations
16.
Helmuth, Thomas, Nicholas Freitag McPhee, & Lee Spector. (2016). Effects of Lexicase and Tournament Selection on Diversity Recovery and Maintenance. 983–990. 16 indexed citations
17.
Helmuth, Thomas & Lee Spector. (2015). General Program Synthesis Benchmark Suite. 1039–1046. 82 indexed citations
18.
Liskowski, Paweł, Krzysztof Krawiec, Thomas Helmuth, & Lee Spector. (2015). Comparison of Semantic-aware Selection Methods in Genetic Programming. 1301–1307. 20 indexed citations
19.
Spector, Lee, Thomas Helmuth, & Kyle Harrington. (2011). Fecundity and selectivity in evolutionary computation. 129–130. 1 indexed citations
20.
Helmuth, Thomas, Lee Spector, & Brian Martin. (2011). Size-based tournaments for node selection. 799–802. 3 indexed citations

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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