Maya Paczuski

5.6k total citations
86 papers, 3.9k citations indexed

About

Maya Paczuski is a scholar working on Condensed Matter Physics, Economics and Econometrics and Statistical and Nonlinear Physics. According to data from OpenAlex, Maya Paczuski has authored 86 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Condensed Matter Physics, 29 papers in Economics and Econometrics and 27 papers in Statistical and Nonlinear Physics. Recurrent topics in Maya Paczuski's work include Theoretical and Computational Physics (46 papers), Complex Systems and Time Series Analysis (29 papers) and Complex Network Analysis Techniques (22 papers). Maya Paczuski is often cited by papers focused on Theoretical and Computational Physics (46 papers), Complex Systems and Time Series Analysis (29 papers) and Complex Network Analysis Techniques (22 papers). Maya Paczuski collaborates with scholars based in United States, Canada and United Kingdom. Maya Paczuski's co-authors include Per Bak, Marco Baiesi, Sergei Maslov, Peter Grassberger, Stefan Boettcher, Kai Nagel, Mehran Kardar, Jörn Davidsen, Kevin E. Bassler and Martín Shubik and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Physical review. B, Condensed matter.

In The Last Decade

Maya Paczuski

86 papers receiving 3.8k citations

Peers

Maya Paczuski
Comparison fields: 5 of 151
  • Condensed Matter Physics 1.4k
  • Statistical and Nonlinear Physics 1.2k
  • Economics and Econometrics 1.1k
  • Geophysics 563
  • Mathematical Physics 541
Replace Kim Christensen with:
Kim Christensen United Kingdom
Hideki Takayasu Japan
L. de Arcangelis Italy
Bikas K. Chakrabarti India
W. Ebeling Germany
Mogens H. Jensen Denmark
Barbara Drossel Germany
Kan Chen United States
R. G. Palmer United States
Álvaro Corral Spain
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Citations per field, relative to Maya Paczuski
Maya Paczuski · 1×
Citations per year, relative to Maya Paczuski
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Countries citing papers authored by Maya Paczuski

Since Specialization
Citations

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

Fields of papers citing papers by Maya Paczuski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maya Paczuski

This figure shows the co-authorship network connecting the top 25 collaborators of Maya Paczuski. A scholar is included among the top collaborators of Maya Paczuski based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Maya Paczuski. Maya Paczuski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 6
2 52
3 16
4 6
5 54
6 37
7 59
8 11
9 51
10 18
11 71
12
Intensity Thresholds and Superstatistics in the Temporal Occurrence of Solar Flares
2
13 63
14 36
15 40
16 26
17 56
18 25
19 12
20
Complexity and extremal dynamics
1

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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