Mikhail Prokopenko
- Statistical and Nonlinear Physics top 0.5%
- Complex Network Analysis Techniques 23
- Opinion Dynamics and Social Influence 14
- Advanced Thermodynamics and Statistical Mechanics 13
- stochastic dynamics and bifurcation 9
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies 14
- Cognitive Neuroscience top 2%
- Neural dynamics and brain function 19
- Economics and Econometrics top 2%
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- Cellular Automata and Applications 16
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- Gene Regulatory Network Analysis 10
- Co-authors
- Joseph T. LizierAlbert Y. ZomayaMahendra PiraveenanX. Rosalind WangSheryl L. ChangFabio BoschettiRichard E. SpinneyAlex Ryan
- Partner nations
- AustraliaGermanyUnited Kingdom
In The Last Decade
Mikhail Prokopenko
123 papers receiving 3.1k citations
Peers
Comparison fields: 5 of 181
- Statistical and Nonlinear Physics 954
- Modeling and Simulation 305
- Cognitive Neuroscience 742
- Economics and Econometrics 398
- Computational Theory and Mathematics 220
Countries citing papers authored by Mikhail Prokopenko
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
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-authorship network
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.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 1 | |
| 4 | 2023 | 7 | |
| 5 | 2023 | 4 | |
| 6 | 2021 | 7 | |
| 7 | 2020 | 19 | |
| 8 | 2020 | 111 | |
| 9 | 2020 | 5 | |
| 10 | 2019 | 27 | |
| 11 | 2018 | 35 | |
| 12 | 2018 | 2 | |
| 13 | 2016 | 5 | |
| 14 | A Fisher Information Study of Phase Transitions in Random Boolean Networks | 2010 | 4 |
| 15 | Modelling Stigmergic Gene Transfer | 2008 | 1 |
| 16 | Emergence of Glider-like Structures in a Modular Robotic System | 2008 | 8 |
| 17 | Optimizing Associative Information Transfer within Content-addressable Memory | 2008 | 1 |
| 18 | Advances in Applied Self-organizing Systems (Advanced Information and Knowledge Processing) | 2007 | 3 |
| 19 | Relating the entropy of joint beliefs to multi-agent coordination | 2003 | 7 |
| 20 | Preferential Semantics for Causal Systems | 1999 | 5 |
About Mikhail Prokopenko
Mikhail Prokopenko is a scholar working on Statistical and Nonlinear Physics, Modeling and Simulation, Computational Theory and Mathematics, Cognitive Neuroscience and Computer Networks and Communications, having authored 128 papers that have together received 3.2k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (23 papers), Neural dynamics and brain function (19 papers), Cellular Automata and Applications (16 papers), COVID-19 epidemiological studies (14 papers), Opinion Dynamics and Social Influence (14 papers), Advanced Thermodynamics and Statistical Mechanics (13 papers), Gene Regulatory Network Analysis (10 papers) and stochastic dynamics and bifurcation (9 papers). The work is most often cited by research in Statistical and Nonlinear Physics (954 citations), Modeling and Simulation (305 citations), Cognitive Neuroscience (742 citations), Economics and Econometrics (398 citations) and Computational Theory and Mathematics (220 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, Sheryl L. Chang, Fabio Boschetti, Richard E. Spinney, Alex Ryan, Liaquat Hossain and Oliver Obst. Their work appears in journals such as Artificial Life, Physical review. E, Scientific Reports, PLoS ONE and Theory in Biosciences.
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.