Moshe Sipper

5.3k citations
143 papers · 2.6k indexed · h-index 26

Impact in

    • Cellular Automata and Applications
    • Computability, Logic, AI Algorithms
    • Evolutionary Algorithms and Applications
    • Metaheuristic Optimization Algorithms Research
    • Neural Networks and Applications
    • Fuzzy Logic and Control Systems

Papers in

    • Evolutionary Algorithms and Applications 75
    • Metaheuristic Optimization Algorithms Research 31
    • Artificial Intelligence in Games 18
    • Neural Networks and Applications 12
    • Cellular Automata and Applications 46
    • Computability, Logic, AI Algorithms 12

Moshe Sipper

132 papers receiving 2.5k citations

Peers

Moshe Sipper
Comparison fields: 5 of 154
  • Computational Theory and Mathematics 952
  • Artificial Intelligence 1.5k
  • Software 61
  • Health Information Management 68
  • Hardware and Architecture 94
Replace Sanguthevar Rajasekaran with:
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Moshe Sipper relative to Sanguthevar Rajasekaran United States Sanguthevar Rajasekaran's profile →
Citations per field
00.5×4.3×
Sanguthevar Rajasekaran · 1×
Citations per year

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-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 143 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999263
2 1997127
3 1997125
4 2000120
5 1998114
6 2000105
7 200094
8 200193
9 199975
10 199972
11 201158
12 201857
13 199656
14 199653
15 199650
16 200149
17
Towards Robust Integrated Circuits: The Embryonics Approach
200047
18 199645
19 199943
20 199935

About Moshe Sipper

Moshe Sipper is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Molecular Biology, Mechanical Engineering and Computer Networks and Communications, having authored 143 papers that have together received 2.6k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (75 papers), Cellular Automata and Applications (46 papers), Metaheuristic Optimization Algorithms Research (31 papers), Modular Robots and Swarm Intelligence (20 papers), DNA and Biological Computing (19 papers), Artificial Intelligence in Games (18 papers), Neural Networks and Applications (12 papers) and Computability, Logic, AI Algorithms (12 papers). The work is most often cited by research in Computational Theory and Mathematics (952 citations), Artificial Intelligence (1.5k citations), Software (61 citations), Health Information Management (68 citations) and Hardware and Architecture (94 citations). Moshe Sipper has collaborated with scholars based in Israel, Switzerland and United States. Frequent 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. Their work appears in journals such as Artificial Life, Genetic Programming and Evolvable Machines, International Journal of Modern Physics C, Computer and IEEE Transactions on Evolutionary Computation.

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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