Moshe Sipper

5.3k total citations
143 papers, 2.6k citations indexed

About

Moshe Sipper is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, Moshe Sipper has authored 143 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 102 papers in Artificial Intelligence, 59 papers in Computational Theory and Mathematics and 30 papers in Molecular Biology. Recurrent topics in Moshe Sipper's work include Evolutionary Algorithms and Applications (75 papers), Cellular Automata and Applications (46 papers) and Metaheuristic Optimization Algorithms Research (31 papers). Moshe Sipper is often cited by papers focused on Evolutionary Algorithms and Applications (75 papers), Cellular Automata and Applications (46 papers) and Metaheuristic Optimization Algorithms Research (31 papers). Moshe Sipper collaborates with scholars based in Israel, Switzerland and United States. Moshe Sipper's co-authors include Carlos Andrés Peña-Reyes, André Stauffer, Marco Tomassini, Daniel Mange, Jason H. Moore, Mathieu S. Capcarrère, Gianluca Tempesti, Marco Tomassini, Eduardo García Sánchez and Andrés Pérez-Uribe and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Moshe Sipper

132 papers receiving 2.5k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Moshe Sipper Israel	26	1.5k	952	758	433	250	143	2.6k
Conor Ryan Ireland	21	1.6k 1.1×	275 0.3×	400 0.5×	139 0.3×	167 0.7×	190	2.7k
Sanguthevar Rajasekaran United States	29	1.2k 0.8×	554 0.6×	1.1k 1.4×	168 0.4×	734 2.9×	266	3.6k
James E. Baker United States	12	846 0.6×	415 0.4×	111 0.1×	124 0.3×	186 0.7×	47	2.2k
Sridhar Mahadevan United States	30	2.4k 1.6×	428 0.4×	140 0.2×	147 0.3×	377 1.5×	115	3.9k
Marc Parizeau Canada	22	831 0.6×	320 0.3×	150 0.2×	118 0.3×	260 1.0×	52	2.4k
Julian F. Miller United Kingdom	24	1.7k 1.2×	237 0.2×	653 0.9×	92 0.2×	74 0.3×	104	2.1k
William F. Punch United States	27	2.3k 1.6×	463 0.5×	498 0.7×	108 0.2×	170 0.7×	81	3.8k
Peter J. Angeline United States	16	1.6k 1.1×	360 0.4×	180 0.2×	93 0.2×	100 0.4×	46	2.2k
Hitoshi Iba Japan	21	1.5k 1.0×	678 0.7×	578 0.8×	66 0.2×	87 0.3×	81	2.6k
Heitor Silvério Lopes Brazil	21	1.6k 1.1×	361 0.4×	348 0.5×	79 0.2×	280 1.1×	148	2.5k

Countries citing papers authored by Moshe Sipper

Since Specialization

Citations

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

Fields of papers citing papers by Moshe Sipper

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Moshe Sipper

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Sipper, Moshe, et al.. (2025). BERT Mutation: Deep Transformer Model for Masked Uniform Mutation in Genetic Programming. Mathematics. 13(5). 779–779.

Sipper, Moshe, et al.. (2024). Open Sesame! Universal Black-Box Jailbreaking of Large Language Models. Applied Sciences. 14(16). 7150–7150. 21 indexed citations

Sipper, Moshe, et al.. (2024). Fortify the Guardian, Not the Treasure: Resilient Adversarial Detectors. Mathematics. 12(22). 3451–3451. 2 indexed citations

Sipper, Moshe, et al.. (2023). EC-KitY: Evolutionary computation tool kit in Python with seamless machine learning integration. SoftwareX. 22. 101381–101381. 6 indexed citations

Sipper, Moshe, et al.. (2022). An Evolutionary, Gradient-Free, Query-Efficient, Black-Box Algorithm for Generating Adversarial Instances in Deep Convolutional Neural Networks. Algorithms. 15(11). 407–407. 3 indexed citations

Sipper, Moshe. (2022). High Per Parameter: A Large-Scale Study of Hyperparameter Tuning for Machine Learning Algorithms. Algorithms. 15(9). 315–315. 20 indexed citations

Sipper, Moshe, et al.. (2022). From Requirements to Source Code: Evolution of Behavioral Programs. Applied Sciences. 12(3). 1587–1587. 3 indexed citations

Sipper, Moshe. (2022). Combining Deep Learning with Good Old-Fashioned Machine Learning. SN Computer Science. 4(1).

Sipper, Moshe & Jason H. Moore. (2021). Symbolic-regression boosting. Genetic Programming and Evolvable Machines. 22(3). 357–381. 4 indexed citations

10.

Sipper, Moshe. (2021). Neural Networks with À La Carte Selection of Activation Functions. SN Computer Science. 2(6). 6 indexed citations

11.

Sipper, Moshe & Jason H. Moore. (2019). OMNIREP: originating meaning by coevolving encodings and representations. Memetic Computing. 11(3). 251–261. 2 indexed citations

12.

Sipper, Moshe & Jason H. Moore. (2019). Genetic programming theory and practice: a fifteen-year trajectory. Genetic Programming and Evolvable Machines. 21(1-2). 169–179. 4 indexed citations

13.

Moore, Jason H., Randal S. Olson, Yong Chen, & Moshe Sipper. (2018). Automated discovery of test statistics using genetic programming. Genetic Programming and Evolvable Machines. 20(1). 127–137. 2 indexed citations

14.

Sipper, Moshe, et al.. (2018). Investigating the parameter space of evolutionary algorithms. BioData Mining. 11(1). 2–2. 57 indexed citations

15.

Orzechowski, Patryk, Moshe Sipper, Xiuzhen Huang, & Jason H. Moore. (2018). EBIC: an artificial intelligence-based parallel biclustering algorithm for pattern discovery.. arXiv (Cornell University). 4 indexed citations

16.

Sipper, Moshe & Jason H. Moore. (2017). Artificial intelligence: more human with human. BioData Mining. 10(1). 34–34. 3 indexed citations

17.

Sipper, Moshe. (2001). On the origin of environments by means of natural selection. AI Magazine. 22(4). 133–140. 4 indexed citations

18.

Sipper, Moshe. (2000). A success story or an old wives' tale? On judging experiments in evolutionary computation. Complexity. 5(4). 31–34. 3 indexed citations

19.

Teuscher, Christof, et al.. (1999). Romero's Pilgrimage to Santa Fe: A Tale of Robot Evolution. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 409–410. 2 indexed citations

20.

Sipper, Moshe, et al.. (1999). Why must computers make us feel blue, see red, turn white, and black out?. IEEE Spectrum. 36(9). 28–31. 1 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.

Explore authors with similar magnitude of impact