Peter Klimek
Impact in
- Modeling and Simulation top 0.2%
- COVID-19 epidemiological studies
-
- Complex Network Analysis Techniques
Papers in
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- COVID-19 epidemiological studies 12
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- Complex Network Analysis Techniques 9
- Opinion Dynamics and Social Influence 4
- Co-authors
- Stefan Thurner (68 shared papers)Rudolf Hanel (7 shared papers)Elma Dervić (13 shared papers)Nils Haug (5 shared papers)Beate Conrady (2 shared papers)Amélie Desvars-Larrive (2 shared papers)Vittorio Loreto (1 shared paper)Lukas Geyrhofer (1 shared paper)
- Journals
- Scientific Reports (8 papers)PLoS ONE (8 papers)Journal of Personalized Medicine (5 papers)New Journal of Physics (5 papers)Proceedings of the National Academy of Sciences (4 papers)
- Partner nations
- AustriaUnited StatesSweden
In The Last Decade
Peter Klimek
121 papers receiving 3.8k citations
Peter Klimek's Hit Papers
Peers
Comparison fields: 5 of 194
- Modeling and Simulation 750
- Statistical and Nonlinear Physics 365
- Internal Medicine 93
- Infectious Diseases 272
- Economics and Econometrics 276
Countries citing papers authored by Peter Klimek
This map shows the geographic impact of Peter Klimek'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 Peter Klimek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Klimek more than expected).
Fields of papers citing papers by Peter Klimek
This network shows the impact of papers produced by Peter Klimek. 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 Peter Klimek. The network helps show where Peter Klimek may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Klimek, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 131 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Ranking the effectiveness of worldwide COVID-19 government interventions Hit paper breakdown → | 2020 | 1021 |
| 2 | Introduction to the Theory of Complex Systems Hit paper breakdown → | 2018 | 264 |
| 3 | 2022 | 144 | |
| 4 | 2021 | 108 | |
| 5 | 2020 | 103 | |
| 6 | 2021 | 91 | |
| 7 | 2021 | 88 | |
| 8 | 2012 | 87 | |
| 9 | 2013 | 82 | |
| 10 | 2020 | 76 | |
| 11 | 2013 | 75 | |
| 12 | 2021 | 68 | |
| 13 | 2020 | 64 | |
| 14 | 2015 | 63 | |
| 15 | 2019 | 63 | |
| 16 | 2020 | 63 | |
| 17 | 2014 | 61 | |
| 18 | 2023 | 58 | |
| 19 | 2022 | 55 | |
| 20 | 2023 | 54 |
About Peter Klimek
Peter Klimek is a scholar working on Modeling and Simulation, Statistical and Nonlinear Physics, Clinical Psychology, Health Information Management and Endocrinology, Diabetes and Metabolism, having authored 131 papers that have together received 3.9k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (12 papers), Complex Network Analysis Techniques (9 papers), Migration, Health and Trauma (7 papers), Chronic Disease Management Strategies (7 papers), Infrastructure Resilience and Vulnerability Analysis (6 papers), Electronic Health Records Systems (5 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers) and Opinion Dynamics and Social Influence (4 papers). The work is most often cited by research in Modeling and Simulation (750 citations), Statistical and Nonlinear Physics (365 citations), Internal Medicine (93 citations), Infectious Diseases (272 citations) and Economics and Econometrics (276 citations). Peter Klimek has collaborated with scholars based in Austria, United States and Sweden. Frequent co-authors include Stefan Thurner, Rudolf Hanel, Elma Dervić, Nils Haug, Beate Conrady, Amélie Desvars-Larrive, Vittorio Loreto, Lukas Geyrhofer, Alessandro Londei and Alexandra Kautzky‐Willer. Their work appears in journals such as Scientific Reports, PLoS ONE, Journal of Personalized Medicine, New Journal of Physics and Proceedings of the National Academy of Sciences.
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.