Attila Kaszás

1.7k citations
31 papers · 1.1k indexed · h-index 16
Topics
Neuroscience and Neural Engineering (16 papers)Neuroscience and Neuropharmacology Research (10 papers)Neural dynamics and brain function (8 papers)

In The Last Decade

Attila Kaszás

28 papers receiving 1.1k citations

Peers

Attila Kaszás
Comparison fields: 5 of 92
  • Cellular and Molecular Neuroscience 680
  • Cognitive Neuroscience 402
  • Biomedical Engineering 286
  • Biophysics 225
  • Electrical and Electronic Engineering 190
Replace Kaiyu Zheng with:
Kaiyu Zheng United Kingdom
Dries Braeken Belgium
Ramin Pashaie United States
Gergely Katona Hungary
Daniel R. Hochbaum United States
Torsten Bullmann Germany
Axel Blau Italy
Darren J. Michael United States
Ulrich Egert Germany
Luca Berdondini Italy
Attila Kaszás relative to Kaiyu Zheng United Kingdom Kaiyu Zheng's profile →
Citations per field
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Citations per year

Countries citing papers authored by Attila Kaszás

Since Specialization
Citations

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

Fields of papers citing papers by Attila Kaszás

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Attila Kaszás

This figure shows the co-authorship network connecting the top 25 collaborators of Attila Kaszás. A scholar is included among the top collaborators of Attila Kaszás 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 Attila Kaszás. Attila Kaszás 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 18
5 18
6 0
7 22
8 6
9 6
10 53
11 147
12 2
13 70
14 12
15 270
16 12
17 23
18 20
19 3
20 25

About Attila Kaszás

Attila Kaszás is a scholar working on Cellular and Molecular Neuroscience, Biophysics and Cognitive Neuroscience, having authored 31 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (16 papers), Neuroscience and Neuropharmacology Research (10 papers) and Neural dynamics and brain function (8 papers). The work is most often cited by research in Biophysics (225 citations), Cellular and Molecular Neuroscience (680 citations) and Cognitive Neuroscience (402 citations). Attila Kaszás has collaborated with scholars based in Hungary, France and United States. Frequent co-authors include Balázs Rózsa, Gergely Katona, Gergely Szalay, E. Sylvester Vizi, Adam Williamson, Balázs Chiovini, George G. Malliaras, Christophe Bernard, Pál Maák and Andrea Slézia. Their work appears in journals such as Proceedings of the National Academy of Sciences, Advanced Materials and Nature Communications.

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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