Árpád Bűrmen
Impact in
- Numerical Analysis top 10%
- Advanced Optimization Algorithms Research
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- Advanced Multi-Objective Optimization Algorithms
Papers in
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- VLSI and FPGA Design Techniques 15
- Low-power high-performance VLSI design 10
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- Metaheuristic Optimization Algorithms Research 11
- Evolutionary Algorithms and Applications 9
- Co-authors
- Benjamin Lipovšek (1 shared paper)Matevž Kunaver (3 shared papers)Vanja Subotić (1 shared paper)Marija Bogataj (1 shared paper)Igor Locatelli (1 shared paper)Mark Žic (1 shared paper)Aleš Mrhar (1 shared paper)Sašo Tomažič (1 shared paper)
In The Last Decade
Árpád Bűrmen
31 papers receiving 268 citations
Peers
Comparison fields: 5 of 77
- Numerical Analysis 42
- Computational Theory and Mathematics 90
- Artificial Intelligence 133
- Hardware and Architecture 18
- Electrical and Electronic Engineering 113
Countries citing papers authored by Árpád Bűrmen
This map shows the geographic impact of Árpád Bűrmen'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 Árpád Bűrmen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Árpád Bűrmen more than expected).
Fields of papers citing papers by Árpád Bűrmen
This network shows the impact of papers produced by Árpád Bűrmen. 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 Árpád Bűrmen. The network helps show where Árpád Bűrmen may publish in the future.
Co-authors
The 8 scholars most cited alongside Árpád Bűrmen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 39 | |
| 2 | 2010 | 33 | |
| 3 | 2006 | 31 | |
| 4 | 2016 | 30 | |
| 5 | 2018 | 19 | |
| 6 | 2009 | 15 | |
| 7 | 2003 | 12 | |
| 8 | 2008 | 12 | |
| 9 | 2003 | 11 | |
| 10 | 2004 | 9 | |
| 11 | 2017 | 8 | |
| 12 | 2021 | 6 | |
| 13 | 2022 | 6 | |
| 14 | 2008 | 6 | |
| 15 | 2014 | 5 | |
| 16 | 2019 | 5 | |
| 17 | 2018 | 5 | |
| 18 | 2010 | 4 | |
| 19 | 2015 | 3 | |
| 20 | 2014 | 3 |
About Árpád Bűrmen
Árpád Bűrmen is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Computational Theory and Mathematics, Numerical Analysis and Hardware and Architecture, having authored 35 papers that have together received 280 indexed citations. Recurring topics across this work include VLSI and FPGA Design Techniques (15 papers), Metaheuristic Optimization Algorithms Research (11 papers), Low-power high-performance VLSI design (10 papers), Advanced Optimization Algorithms Research (10 papers), Evolutionary Algorithms and Applications (9 papers), Advanced Multi-Objective Optimization Algorithms (9 papers), VLSI and Analog Circuit Testing (4 papers) and Numerical Methods and Algorithms (3 papers). The work is most often cited by research in Numerical Analysis (42 citations), Computational Theory and Mathematics (90 citations), Artificial Intelligence (133 citations), Hardware and Architecture (18 citations) and Electrical and Electronic Engineering (113 citations). Árpád Bűrmen has collaborated with scholars based in Slovenia, Australia and Croatia. Frequent co-authors include Benjamin Lipovšek, Matevž Kunaver, Vanja Subotić, Marija Bogataj, Igor Locatelli, Mark Žic, Aleš Mrhar and Sašo Tomažič. Their work appears in journals such as Computational Optimization and Applications, Genetic Programming and Evolvable Machines, Optimization Letters, IEEE photonics journal and Engineering Applications of Artificial Intelligence.
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.