Phillip Schumm
Impact in
-
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies
Papers in
-
- Complex Network Analysis Techniques 10
-
- Animal Disease Management and Epidemiology 3
- Co-authors
- Caterina Scoglio (15 shared papers)Sakshi Pahwa (1 shared paper)Stojan Trajanovski (1 shared paper)Xin Ge (1 shared paper)Noel N. Schulz (1 shared paper)H. Wang (1 shared paper)Piet Van Mieghem (1 shared paper)Todd Easton (2 shared papers)
- Journals
- Journal of Theoretical Biology (3 papers)PLoS ONE (2 papers)Journal of Computational Science (1 paper)Implementation Science (1 paper)Physica A Statistical Mechanics and its Applications (1 paper)
- Partner nations
- United StatesNetherlandsTürkiye
In The Last Decade
Phillip Schumm
15 papers receiving 252 citations
Peers
Comparison fields: 5 of 74
- Statistical and Nonlinear Physics 118
- Modeling and Simulation 28
- Geometry and Topology 26
- Computer Networks and Communications 53
- Agronomy and Crop Science 21
Countries citing papers authored by Phillip Schumm
This map shows the geographic impact of Phillip Schumm'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 Phillip Schumm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phillip Schumm more than expected).
Fields of papers citing papers by Phillip Schumm
This network shows the impact of papers produced by Phillip Schumm. 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 Phillip Schumm. The network helps show where Phillip Schumm may publish in the future.
Co-authors
The 18 scholars most cited alongside Phillip Schumm, 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 | 2013 | 46 | |
| 2 | 2010 | 43 | |
| 3 | 2010 | 32 | |
| 4 | 2010 | 22 | |
| 5 | 2007 | 21 | |
| 6 | 2009 | 18 | |
| 7 | 2008 | 17 | |
| 8 | 2011 | 16 | |
| 9 | 2012 | 11 | |
| 10 | 2009 | 9 | |
| 11 | 2015 | 9 | |
| 12 | 2012 | 7 | |
| 13 | 2013 | 6 | |
| 14 | 2014 | 2 | |
| 15 | 2013 | 1 | |
| 16 | Elasticity and Viral Conductance: Unveiling Robustness in Complex Networks through Topological Characteristics | 2008 | 0 |
About Phillip Schumm
Phillip Schumm is a scholar working on Statistical and Nonlinear Physics, Agronomy and Crop Science, Genetics, Modeling and Simulation and Molecular Biology, having authored 16 papers that have together received 260 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (10 papers), COVID-19 epidemiological studies (3 papers), Animal Disease Management and Epidemiology (3 papers), Mathematical and Theoretical Epidemiology and Ecology Models (2 papers), Evolution and Genetic Dynamics (2 papers), Gene Regulatory Network Analysis (2 papers), Evolutionary Game Theory and Cooperation (2 papers) and Genetic and phenotypic traits in livestock (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (118 citations), Modeling and Simulation (28 citations), Geometry and Topology (26 citations), Computer Networks and Communications (53 citations) and Agronomy and Crop Science (21 citations). Phillip Schumm has collaborated with scholars based in United States, Netherlands and Türkiye. Frequent co-authors include Caterina Scoglio, Sakshi Pahwa, Stojan Trajanovski, Xin Ge, Noel N. Schulz, H. Wang, Piet Van Mieghem, Todd Easton, Walter R. Schumm and Don Gruenbacher. Their work appears in journals such as Journal of Theoretical Biology, PLoS ONE, Journal of Computational Science, Implementation Science and Physica A Statistical Mechanics and its Applications.
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.