Ágnes Vathy-Fogarassy

556 citations
44 papers · 315 indexed · h-index 10
Topics
Vehicle Dynamics and Control Systems (4 papers)Advanced Clustering Algorithms Research (4 papers)Biomedical Text Mining and Ontologies (4 papers)
Journals
SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports

In The Last Decade

Ágnes Vathy-Fogarassy

40 papers receiving 301 citations

Peers

Ágnes Vathy-Fogarassy
Comparison fields: 5 of 109
  • Artificial Intelligence 77
  • Computer Networks and Communications 38
  • Molecular Biology 37
  • Control and Systems Engineering 37
  • Information Systems 36
Replace Sudhakar Kumar with:
Sudhakar Kumar India
Yi Zhuang China
Matthias Steinbrecher Germany
Mervat Abu-Elkheir Egypt
Tariq Alsboui United Kingdom
Mohamed Tounsi Saudi Arabia
Ansaf Salleb-Aouissi United States
Alexander Karlsson Sweden
B. Nagaraj India
Ágnes Vathy-Fogarassy relative to Sudhakar Kumar India Sudhakar Kumar's profile →
Citations per field
00.5×10×20×33×
Sudhakar Kumar · 1×
Citations per year

Countries citing papers authored by Ágnes Vathy-Fogarassy

Since Specialization
Citations

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

Fields of papers citing papers by Ágnes Vathy-Fogarassy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ágnes Vathy-Fogarassy. 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 Ágnes Vathy-Fogarassy. The network helps show where Ágnes Vathy-Fogarassy may publish in the future.

Co-authorship network of co-authors of Ágnes Vathy-Fogarassy

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 2
5 1
6 0
7 27
8 8
9 5
10 3
11 7
12 14
13 9
14 2
15 2
16 4
17 30
18 3
19 33
20
Virtual Reality Simulations in the Education of Mathematics and Physics
1

About Ágnes Vathy-Fogarassy

Ágnes Vathy-Fogarassy is a scholar working on Artificial Intelligence, Statistics and Probability and Information Systems, having authored 44 papers that have together received 315 indexed citations. Recurring topics across this work include Vehicle Dynamics and Control Systems (4 papers), Advanced Clustering Algorithms Research (4 papers) and Biomedical Text Mining and Ontologies (4 papers). The work is most often cited by research in Management Information Systems (24 citations), Industrial and Manufacturing Engineering (24 citations) and Artificial Intelligence (77 citations). Ágnes Vathy-Fogarassy has collaborated with scholars based in Hungary, United Kingdom and Switzerland. Frequent co-authors include János Abonyi, István Kenessey, Tamás Forster, Miklós Kásler, István Kósa, Krisztina Tóth, István Vassányi, Balázs Feil, Csaba Polgár and Péter Nagy. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

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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