Roman Neruda

964 citations
92 papers · 476 · h-index 11

Impact in

    • Metaheuristic Optimization Algorithms Research
    • Evolutionary Algorithms and Applications
    • Neural Networks and Applications
    • Machine Learning and Data Classification
    • Adversarial Robustness in Machine Learning
    • Advanced Multi-Objective Optimization Algorithms

Papers in

    • Metaheuristic Optimization Algorithms Research 36
    • Evolutionary Algorithms and Applications 27
    • Neural Networks and Applications 17
    • Machine Learning and Data Classification 15
    • Multi-Agent Systems and Negotiation 7
    • Semantic Web and Ontologies 7
    • Advanced Multi-Objective Optimization Algorithms 21

Roman Neruda

84 papers receiving 454 citations

Peers

Roman Neruda
Comparison fields: 5 of 85
  • Artificial Intelligence 331
  • Computational Theory and Mathematics 146
  • Management Science and Operations Research 47
  • Information Systems 79
  • Signal Processing 32
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Márcio P. Basgalupp Brazil
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Citations per field
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Citations per year

Countries citing papers authored by Roman Neruda

Since Specialization
Citations

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

Fields of papers citing papers by Roman Neruda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Roman Neruda, 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 Roman Neruda Line = papers co-authored together Roman Neruda links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 92 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200457
2 201221
3 201720
4 200820
5 202019
6 201119
7 202218
8 201116
9 201215
10 200914
11 201511
12 201510
13 20169
14 20149
15 20168
16 20138
17 20068
18
Evolution Strategies for Deep Neural Network Models Design.
20177
19 20127
20
Proceedings of the 18th international conference on Artificial Neural Networks, Part II
20087

About Roman Neruda

Roman Neruda is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Information Systems, Computer Networks and Communications and Control and Systems Engineering, having authored 92 papers that have together received 476 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (36 papers), Evolutionary Algorithms and Applications (27 papers), Advanced Multi-Objective Optimization Algorithms (21 papers), Neural Networks and Applications (17 papers), Machine Learning and Data Classification (15 papers), Data Mining Algorithms and Applications (10 papers), Multi-Agent Systems and Negotiation (7 papers) and Semantic Web and Ontologies (7 papers). The work is most often cited by research in Artificial Intelligence (331 citations), Computational Theory and Mathematics (146 citations), Management Science and Operations Research (47 citations), Information Systems (79 citations) and Signal Processing (32 citations). Roman Neruda has collaborated with scholars based in Czechia, United States and Colombia. Frequent co-authors include Roman Vaculín, Katia Sycara, Juan Carlos Figueroa–García, Huajun Chen, Pavel Krömer, Miguel Á. Vega-Rodríguez, Věra Kůrková, Carlos Martı́n-Vide, Václav Snåšel and Jan Koutník. Their work appears in journals such as Neural Networks, Scientific Reports, Engineering Applications of Artificial Intelligence, Information Sciences and Neurocomputing.

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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