Dániel Kozma

639 citations
19 papers · 446 · h-index 11

Impact in

Papers in

Dániel Kozma

18 papers receiving 439 citations

Peers

Dániel Kozma
Comparison fields: 5 of 81
  • Industrial and Manufacturing Engineering 118
  • Management Information Systems 41
  • Molecular Biology 227
  • Computer Networks and Communications 59
  • Management of Technology and Innovation 18
Replace Moon Jung Chung with:
Moon Jung Chung United States
Zalmiyah Zakaria Malaysia
Azam Sheikh Muhammad Sweden
Jenny Xu United States
Dave Corne United Kingdom
Zoé Lacroix United States
Giuseppe Lancia Italy
Gunnar Mathiason Sweden
Alfonso E. Márquez-Chamorro Spain
Mohamed Khalgui Tunisia
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Citations per field
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Citations per year

Countries citing papers authored by Dániel Kozma

Since Specialization
Citations

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

Fields of papers citing papers by Dániel Kozma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside Dániel Kozma, 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 Dániel Kozma Line = papers co-authored together Dániel Kozma links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2012199
2 202030
3 201627
4 201927
5 201223
6 201919
7 201917
8 201115
9 202115
10 201812
11 201811
12 201910
13 202010
14 20159
15 20158
16 20207
17 20236
18 20171
19 20120

About Dániel Kozma

Dániel Kozma is a scholar working on Industrial and Manufacturing Engineering, Management Information Systems, Computer Networks and Communications, Molecular Biology and Information Systems, having authored 19 papers that have together received 446 indexed citations. Recurring topics across this work include Digital Transformation in Industry (7 papers), Flexible and Reconfigurable Manufacturing Systems (5 papers), Business Process Modeling and Analysis (4 papers), Protein Structure and Dynamics (3 papers), IoT and Edge/Fog Computing (3 papers), RNA and protein synthesis mechanisms (3 papers), Service-Oriented Architecture and Web Services (3 papers) and Machine Learning in Bioinformatics (2 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (118 citations), Management Information Systems (41 citations), Molecular Biology (227 citations), Computer Networks and Communications (59 citations) and Management of Technology and Innovation (18 citations). Dániel Kozma has collaborated with scholars based in Hungary, Spain and Sweden. Frequent co-authors include Gábor Tusnády, István Simon, Pál Varga, Félix Larrinaga, Gábor Soós, Csaba Hegedűs, Dániel Ficzere, Andrea H. Németh, Sándor Kurunczi and Hajnalka Jankovics. Their work appears in journals such as Applied Sciences, Nucleic Acids Research, IEEE Transactions on Automation Science and Engineering, Biology Direct and Applied Surface Science.

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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