Samuel Rudy

26 total papers · 2.1k total citations
17 papers, 1.3k citations indexed

About

Samuel Rudy is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics and Statistics, Probability and Uncertainty. According to data from OpenAlex, Samuel Rudy has authored 17 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computational Mechanics, 8 papers in Statistical and Nonlinear Physics and 6 papers in Statistics, Probability and Uncertainty. Recurrent topics in Samuel Rudy's work include Model Reduction and Neural Networks (8 papers), Fluid Dynamics and Vibration Analysis (6 papers) and Probabilistic and Robust Engineering Design (6 papers). Samuel Rudy is often cited by papers focused on Model Reduction and Neural Networks (8 papers), Fluid Dynamics and Vibration Analysis (6 papers) and Probabilistic and Robust Engineering Design (6 papers). Samuel Rudy collaborates with scholars based in United States, Canada and Brazil. Samuel Rudy's co-authors include J. Nathan Kutz, Steven L. Brunton, Joshua L. Proctor, Alessandro Alla, Themistoklis P. Sapsis, Michael S. Triantafyllou, Dixia Fan, Pedro D. Maia, Ehsan Kharazmi and George Em Karniadakis and has published in prestigious journals such as Journal of Computational Physics, Science Advances and AIAA Journal.

In The Last Decade

Samuel Rudy

15 papers receiving 1.3k citations

Hit Papers

Data-driven discovery of ... 2017 2026 2020 2023 2017 250 500 750

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Samuel Rudy 882 329 288 269 226 17 1.3k
Bethany Lusch 798 0.9× 271 0.8× 479 1.7× 160 0.6× 184 0.8× 25 1.3k
Alexey Radul 654 0.7× 372 1.1× 282 1.0× 124 0.5× 95 0.4× 17 1.4k
Atılım Güneş Baydin 651 0.7× 395 1.2× 283 1.0× 125 0.5× 99 0.4× 18 1.6k
Yibo Yang 634 0.7× 214 0.7× 278 1.0× 141 0.5× 69 0.3× 23 1.1k
Yinhao Zhu 580 0.7× 199 0.6× 297 1.0× 210 0.8× 70 0.3× 16 1.4k
Justin Sirignano 962 1.1× 244 0.7× 434 1.5× 187 0.7× 53 0.2× 16 1.4k
Konstantinos Spiliopoulos 1.0k 1.2× 259 0.8× 445 1.5× 200 0.7× 69 0.3× 44 1.6k
Vincenzo Schiano Di Cola 579 0.7× 316 1.0× 219 0.8× 74 0.3× 116 0.5× 20 1.5k
Minglang Yin 906 1.0× 242 0.7× 469 1.6× 136 0.5× 86 0.4× 14 1.6k
Ehsan Kharazmi 982 1.1× 206 0.6× 455 1.6× 136 0.5× 59 0.3× 15 1.4k

Countries citing papers authored by Samuel Rudy

Since Specialization
Citations

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

Fields of papers citing papers by Samuel Rudy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samuel Rudy

This figure shows the co-authorship network connecting the top 25 collaborators of Samuel Rudy. A scholar is included among the top collaborators of Samuel Rudy based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Samuel Rudy. Samuel Rudy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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