Árpád Bakay

1.7k citations
4 papers · 1.1k indexed · 1 hit paper · h-index 4
Topics
Model-Driven Software Engineering Techniques (3 papers)Advanced Software Engineering Methodologies (3 papers)Peer-to-Peer Network Technologies (1 paper)
Partner nations
AustriaItalyNew Zealand

In The Last Decade

Árpád Bakay

4 papers receiving 957 citations

Hit Papers

Composing domain-specific design environments20012026200920172001200400600

Peers

Árpád Bakay
Comparison fields: 5 of 72
  • Computer Networks and Communications 431
  • Software 390
  • Artificial Intelligence 365
  • Information Systems 273
  • Electrical and Electronic Engineering 218
Replace G. Nordstrom with:
G. Nordstrom United States
Patrizia Scandurra Italy
Paolo Arcaini Japan
Samuel T. Chanson Hong Kong
Shaoying Liu Japan
Lucas C. Cordeiro Brazil
Ricky W. Butler United States
Malathi Veeraraghavan United States
Yulei Sui Australia
Kexin Pei United States
Árpád Bakay relative to G. Nordstrom United States G. Nordstrom's profile →
Citations per field
00.5×1.5×
G. Nordstrom · 1×
Citations per year

Countries citing papers authored by Árpád Bakay

Since Specialization
Citations

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

Fields of papers citing papers by Árpád Bakay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Árpád Bakay

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

All Works

4 of 4 papers shown
#WorkIndexed citations
1 27
2
UDM: An Infrastructure for Implementing Domain-Specific Modeling Languages
16
3
The Generic Modeling Environment
293
4
Composing domain-specific design environmentsbreakdown →
748

About Árpád Bakay

Árpád Bakay is a scholar working on Software, Hardware and Architecture and Artificial Intelligence, having authored 4 papers that have together received 1.1k indexed citations. Recurring topics across this work include Model-Driven Software Engineering Techniques (3 papers), Advanced Software Engineering Methodologies (3 papers) and Peer-to-Peer Network Technologies (1 paper). The work is most often cited by research in Software (390 citations), Hardware and Architecture (179 citations) and Computer Networks and Communications (431 citations). Árpád Bakay has collaborated with scholars based in Austria, Italy and New Zealand. Frequent co-authors include Gábor Karsai, Miklós Maróti, Péter Völgyesi, Jonathan Sprinkle, Ákos Lédeczi, G. Nordstrom, Aditya Agarwal, Luca Muscariello, Emilio Leonardi and Jan Seedorf. Their work appears in journals such as IEEE Communications Magazine and Computer.

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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