Philip E. Paré

64 papers receiving 705 citations

Peers

Philip E. Paré
Comparison fields: 5 of 69
  • Modeling and Simulation 317
  • Statistical and Nonlinear Physics 373
  • Public Health, Environmental and Occupational Health 246
  • Experimental and Cognitive Psychology 48
  • Management Science and Operations Research 37
Replace Faryad Darabi Sahneh with:
Faryad Darabi Sahneh United States
Lorenzo Zino Italy
Liang’an Huo China
Ariel Cintrón-Arias United States
Zhishuang Wang China
Damian A. Knopoff Argentina
Ceyhun Eksin United States
Jasmina Omić Netherlands
Minyu Feng China
Philip E. Paré relative to Faryad Darabi Sahneh United States Faryad Darabi Sahneh's profile →
Citations per field
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Citations per year

Countries citing papers authored by Philip E. Paré

Since Specialization
Citations

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

Fields of papers citing papers by Philip E. Paré

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Philip E. Paré. 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 Philip E. Paré. The network helps show where Philip E. Paré may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 73 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020107
2 201987
3 201860
4 202254
5 202042
6 202026
7 202123
8 201721
9 201920
10 201619
11 201517
12 202314
13 202114
14 201913
15 201811
16 201711
17 201310
18 20179
19 20209
20 20218

About Philip E. Paré

Philip E. Paré is a scholar working on Modeling and Simulation, Statistical and Nonlinear Physics, Public Health, Environmental and Occupational Health, Infectious Diseases and Management Science and Operations Research, having authored 73 papers that have together received 717 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (33 papers), Complex Network Analysis Techniques (32 papers), Mathematical and Theoretical Epidemiology and Ecology Models (26 papers), Opinion Dynamics and Social Influence (19 papers), Influenza Virus Research Studies (6 papers), SARS-CoV-2 and COVID-19 Research (5 papers), Mental Health Research Topics (5 papers) and Evolution and Genetic Dynamics (4 papers). The work is most often cited by research in Modeling and Simulation (317 citations), Statistical and Nonlinear Physics (373 citations), Public Health, Environmental and Occupational Health (246 citations), Experimental and Cognitive Psychology (48 citations) and Management Science and Operations Research (37 citations). Philip E. Paré has collaborated with scholars based in United States, Sweden and China. Frequent co-authors include Carolyn L. Beck, Tamer Başar, Ji yin Liu, Angelia Nedich, Shreyas Sundaram, Choon Yik Tang, Henrik Sandberg, Liu Ji, Barrett E. Kirwan and Karl Henrik Johansson. Their work appears in journals such as IEEE Control Systems Letters, IEEE Transactions on Control of Network Systems, Automatica, IEEE Transactions on Automatic Control and IEEE Transactions on Network Science and Engineering.

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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