Ryan Riegel

764 citations
8 papers · 254 · h-index 4

Impact in

    • Astronomy and Astrophysical Research
    • Galaxies: Formation, Evolution, Phenomena
    • Gamma-ray bursts and supernovae
    • Astrophysical Phenomena and Observations
    • Stellar, planetary, and galactic studies
    • Radio Astronomy Observations and Technology
    • Cosmology and Gravitation Theories

Papers in

    • Bayesian Modeling and Causal Inference 2
    • Logic, Reasoning, and Knowledge 2
    • Neural Networks and Applications 2
    • Remote Sensing in Agriculture 3

Ryan Riegel

7 papers receiving 246 citations

Peers

Ryan Riegel
Comparison fields: 5 of 31
  • Instrumentation 73
  • Astronomy and Astrophysics 214
  • Nuclear and High Energy Physics 50
  • Artificial Intelligence 34
  • Ecology 17
Replace Kate Storey-Fisher with:
Kate Storey-Fisher United States
L. Faccioli France
Mohammadjavad Vakili Netherlands
Anna K. Weigel Switzerland
M. V. Costa-Duarte Brazil
Alex I. Malz United States
Michelle Ntampaka United States
F. Sobreira Brazil
T. Boch France
Caroline Heneka Germany
Ryan Riegel relative to Kate Storey-Fisher United States Kate Storey-Fisher's profile →
Citations per field
00.5×3.7×
Kate Storey-Fisher · 1×
Citations per year

Countries citing papers authored by Ryan Riegel

Since Specialization
Citations

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

Fields of papers citing papers by Ryan Riegel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Ryan Riegel, 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 Ryan Riegel Line = papers co-authored together Ryan Riegel links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 2008187
2 201536
3 202219
4 20087
5 20242
6 20212
7 20121
8 20240

About Ryan Riegel

Ryan Riegel is a scholar working on Artificial Intelligence, Ecology, Computational Theory and Mathematics, Astronomy and Astrophysics and Statistical and Nonlinear Physics, having authored 8 papers that have together received 254 indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (3 papers), Rough Sets and Fuzzy Logic (3 papers), Galaxies: Formation, Evolution, Phenomena (2 papers), Bayesian Modeling and Causal Inference (2 papers), Logic, Reasoning, and Knowledge (2 papers), Neural Networks and Applications (2 papers), Gamma-ray bursts and supernovae (2 papers) and Data Management and Algorithms (1 paper). The work is most often cited by research in Instrumentation (73 citations), Astronomy and Astrophysics (214 citations), Nuclear and High Energy Physics (50 citations), Artificial Intelligence (34 citations) and Ecology (17 citations). Ryan Riegel has collaborated with scholars based in United States, United Kingdom and Ireland. Frequent co-authors include Gordon T. Richards, Adam D. Myers, Alexander Gray, Scott F. Anderson, Donald P. Schneider, Alexander S. Szalay, Róbert Brunner, R. C. Nichol, Prithviraj Sen and Alexander Gray. Their work appears in journals such as The Astrophysical Journal, International Journal of Approximate Reasoning, The Astrophysical Journal Supplement Series, Proceedings of the National Academy of Sciences and Proceedings of the AAAI Conference on Artificial Intelligence.

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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