Mikhail Prokopenko

6.6k citations
181 papers · 4.2k · h-index 33

Impact in

Papers in

Mikhail Prokopenko

172 papers receiving 4.1k citations

Peers

Mikhail Prokopenko
Comparison fields: 5 of 184
  • Statistical and Nonlinear Physics 1.2k
  • Modeling and Simulation 309
  • Cognitive Neuroscience 906
  • Computational Theory and Mathematics 415
  • Artificial Intelligence 762
Replace Manlio De Domenico with:
Manlio De Domenico Italy
Francisco A. Rodrigues Brazil
M. Ángeles Serrano Spain
Peter J. Mucha United States
Zoltán Toroczkai United States
James P. Gleeson Ireland
Kang Hao Cheong Singapore
Desmond J. Higham United Kingdom
Mikko Kivelä Finland
Lucas Lacasa Spain
Mikhail Prokopenko relative to Manlio De Domenico Italy Manlio De Domenico's profile →
Citations per field
00.5×1.5×
Manlio De Domenico · 1×
Citations per year

Countries citing papers authored by Mikhail Prokopenko

Since Specialization
Citations

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

Fields of papers citing papers by Mikhail Prokopenko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 181 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020255
2 2008211
3 2008173
4 2010168
5 2010148
6 2013143
7 2012129
8 2020118
9 201092
10 201389
11 200689
12 201185
13 200977
14 201274
15 201371
16 200870
17 201069
18 201163
19 202260
20 200759

About Mikhail Prokopenko

Mikhail Prokopenko is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Computational Theory and Mathematics, Molecular Biology and Cognitive Neuroscience, having authored 181 papers that have together received 4.2k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (29 papers), Cellular Automata and Applications (25 papers), Neural dynamics and brain function (25 papers), Modular Robots and Swarm Intelligence (19 papers), Opinion Dynamics and Social Influence (19 papers), COVID-19 epidemiological studies (15 papers), Evolutionary Algorithms and Applications (14 papers) and Advanced Thermodynamics and Statistical Mechanics (14 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.2k citations), Modeling and Simulation (309 citations), Cognitive Neuroscience (906 citations), Computational Theory and Mathematics (415 citations) and Artificial Intelligence (762 citations). Mikhail Prokopenko has collaborated with scholars based in Australia, Germany and United Kingdom. Frequent co-authors include Joseph T. Lizier, Albert Y. Zomaya, Mahendra Piraveenan, X. Rosalind Wang, Fabio Boschetti, Alex Ryan, Sheryl L. Chang, Oliver Obst, Liaquat Hossain and Richard E. Spinney. Their work appears in journals such as Artificial Life, Physical review. E, Scientific Reports, Royal Society Open Science and PLoS ONE.

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.

Explore authors with similar magnitude of impact