F. Paul Spitzner

1.1k citations
9 papers · 635 · 1 hit paper · h-index 6

Impact in

Papers in

F. Paul Spitzner

8 papers receiving 627 citations

F. Paul Spitzner's Hit Papers

Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions 2020 · 524 citations
5240+2+4Years since publication100200300400500

Peers

F. Paul Spitzner
Comparison fields: 5 of 98
  • Modeling and Simulation 411
  • Infectious Diseases 127
  • Economics and Econometrics 162
  • Health 31
  • Epidemiology 110
Replace Jonas Dehning with:
Jonas Dehning Germany
João Pinheiro Neto Germany
Johannes Zierenberg Germany
Joshua Teperowski Monrad United States
Sören Mindermann United Kingdom
Mrinank Sharma United Kingdom
Swapnil Mishra United Kingdom
Gavin Leech United Kingdom
Tomáš Gavenčiak Czechia
Tamay Besiroglu United States
F. Paul Spitzner relative to Jonas Dehning Germany Jonas Dehning's profile →
Citations per field
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Jonas Dehning · 1×
Citations per year

Countries citing papers authored by F. Paul Spitzner

Since Specialization
Citations

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

Fields of papers citing papers by F. Paul Spitzner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by F. Paul Spitzner. 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 F. Paul Spitzner. The network helps show where F. Paul Spitzner may publish in the future.

Co-authors

The 21 scholars most cited alongside F. Paul Spitzner, 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 F. Paul Spitzner Line = papers co-authored together F. Paul Spitzner links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions
Hit paper breakdown →
2020524
2 201735
3 202129
4 202323
5 202111
6 20227
7 20243
8 20223
9 20180

About F. Paul Spitzner

F. Paul Spitzner is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience, Condensed Matter Physics, Statistical and Nonlinear Physics and Economics and Econometrics, having authored 9 papers that have together received 635 indexed citations. Recurring topics across this work include Neural dynamics and brain function (4 papers), Neuroscience and Neural Engineering (2 papers), stochastic dynamics and bifurcation (2 papers), Theoretical and Computational Physics (2 papers), COVID-19 epidemiological studies (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Agricultural risk and resilience (1 paper) and Visual perception and processing mechanisms (1 paper). The work is most often cited by research in Modeling and Simulation (411 citations), Infectious Diseases (127 citations), Economics and Econometrics (162 citations), Health (31 citations) and Epidemiology (110 citations). F. Paul Spitzner has collaborated with scholars based in Germany, Spain and Ukraine. Frequent co-authors include Viola Priesemann, Johannes Zierenberg, Jonas Dehning, João Pinheiro Neto, Michael Wilczek, Michael Wibral, Viktoria Blavatska, Wolfhard Janke, Sebastian Mohr and Sebastián Contreras. Their work appears in journals such as Science Advances, PLoS Computational Biology, PLoS ONE, Physical review. E and 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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