Leah B. Shaw

41 papers receiving 1.3k citations

Peers

Leah B. Shaw
Comparison fields: 5 of 114
  • Modeling and Simulation 254
  • Statistical and Nonlinear Physics 429
  • Mathematical Physics 270
  • Condensed Matter Physics 248
  • Statistics and Probability 128
Replace Silvio C. Ferreira with:
Silvio C. Ferreira Brazil
Christian A. Yates United Kingdom
Théodore Kolokolnikov Canada
Chad M. Topaz United States
Guillermo Abramson Argentina
Carlos Escudero Spain
Hernán G. Solari Argentina
J. Radcliffe United Kingdom
Tim Rogers United Kingdom
Aidan Sudbury Australia
Leah B. Shaw relative to Silvio C. Ferreira Brazil Silvio C. Ferreira's profile →
Citations per field
00.5×1.5×
Silvio C. Ferreira · 1×
Citations per year

Countries citing papers authored by Leah B. Shaw

Since Specialization
Citations

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

Fields of papers citing papers by Leah B. Shaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Leah B. Shaw. 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 Leah B. Shaw. The network helps show where Leah B. Shaw may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003248
2 2008185
3 2005128
4 201099
5 200487
6 200370
7 200449
8 201046
9 200645
10 200544
11 200443
12 201135
13 200931
14 201129
15 201223
16 200622
17 200820
18 200719
19 201019
20 196613

About Leah B. Shaw

Leah B. Shaw is a scholar working on Statistical and Nonlinear Physics, Public Health, Environmental and Occupational Health, Genetics, Condensed Matter Physics and Mathematical Physics, having authored 42 papers that have together received 1.4k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (11 papers), Opinion Dynamics and Social Influence (10 papers), Evolution and Genetic Dynamics (9 papers), Mathematical and Theoretical Epidemiology and Ecology Models (8 papers), Theoretical and Computational Physics (6 papers), Stochastic processes and statistical mechanics (6 papers), COVID-19 epidemiological studies (5 papers) and Nonlinear Dynamics and Pattern Formation (4 papers). The work is most often cited by research in Modeling and Simulation (254 citations), Statistical and Nonlinear Physics (429 citations), Mathematical Physics (270 citations), Condensed Matter Physics (248 citations) and Statistics and Probability (128 citations). Leah B. Shaw has collaborated with scholars based in United States, Australia and Brazil. Frequent co-authors include Ira B. Schwartz, Kelvin H. Lee, R. K. P. Zia, Lora Billings, Derek A. T. Cummings, Donald S. Burke, Anatoly B. Kolomeisky, Simone Bianco, James P. Sethna and Bernardo A. Mello. Their work appears in journals such as Journal of Theoretical Biology, Bulletin of Mathematical Biology, Journal of Statistical Physics, Journal of Physics A Mathematical and Theoretical and Chaos An Interdisciplinary Journal of Nonlinear Science.

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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