Robert Repnik

620 citations
49 papers · 459 · h-index 9

Impact in

Papers in

Robert Repnik

43 papers receiving 441 citations

Peers

Robert Repnik
Comparison fields: 5 of 80
  • Statistical and Nonlinear Physics 195
  • Modeling and Simulation 40
  • Computer Networks and Communications 148
  • Cognitive Neuroscience 74
  • Electronic, Optical and Magnetic Materials 51
Replace Mitja Slavinec with:
Mitja Slavinec Slovenia
Daniel J. Velleman United States
Thomas W. Carr United States
Ni Zhang China
Andrés Aragoneses United States
Robert Tchitnga Cameroon
Hanshuang Chen China
Harald Schumny Germany
Sergei Parsegov Russia
Martin M. Stein United States
Robert Repnik relative to Mitja Slavinec Slovenia Mitja Slavinec's profile →
Citations per field
00.5×1.5×
Mitja Slavinec · 1×
Citations per year

Countries citing papers authored by Robert Repnik

Since Specialization
Citations

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

Fields of papers citing papers by Robert Repnik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Robert Repnik, 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 Robert Repnik Line = papers co-authored together Robert Repnik links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019111
2 201987
3 200326
4 201925
5 201925
6 201925
7 201818
8 201315
9 201814
10 20198
11 20208
12 20227
13 20217
14 20207
15 20196
16 20006
17 20156
18 20185
19 20215
20 20194

About Robert Repnik

Robert Repnik is a scholar working on Statistical and Nonlinear Physics, Education, Electronic, Optical and Magnetic Materials, Computer Networks and Communications and Information Systems, having authored 49 papers that have together received 459 indexed citations. Recurring topics across this work include Liquid Crystal Research Advancements (12 papers), Science Education and Pedagogy (10 papers), Nonlinear Dynamics and Pattern Formation (7 papers), Experimental and Theoretical Physics Studies (7 papers), Chaos control and synchronization (5 papers), Mobile Learning in Education (5 papers), Experimental Learning in Engineering (4 papers) and Advanced Materials and Mechanics (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (195 citations), Modeling and Simulation (40 citations), Computer Networks and Communications (148 citations), Cognitive Neuroscience (74 citations) and Electronic, Optical and Magnetic Materials (51 citations). Robert Repnik has collaborated with scholars based in Slovenia, Austria and Iran. Frequent co-authors include Matjaž Perc, Amin Yousefpour, Shaobo He, Hadi Jahanshahi, Sajad Jafari, Fatemeh Parastesh, Boshra Hatef, Hamed Azarnoush, Samo Kralj and Vladimir Grubelnik. Their work appears in journals such as Chaos Solitons & Fractals, Applied Mathematics and Computation, Physical Review Physics Education Research, Journal of Physics Condensed Matter and Energies.

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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