Samuel Rudy

2.1k total citations · 1 hit paper
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, Zhi‐Cheng Wang and Ehsan Kharazmi 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 partial differential equations 2017 2026 2020 2023 2017 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Data-driven discovery of partial differential equations
    2017 931 citations Samuel Rudy, Steven L. Brunton et al. Science Advances profile →

Peers

Samuel Rudy
Bethany Lusch United States
Alexey Radul United States
Hayden Schaeffer United States
Yibo Yang United States
Eurika Kaiser United States
Marko Budišić United States
Jean-Christophe Loiseau France
Saifon Chaturantabut Thailand
John Burkardt United States
Bing Yu China
Bethany Lusch United States
Samuel Rudy
Citations per year, relative to Samuel Rudy Samuel Rudy (= 1×) peers Bethany Lusch

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

17 of 17 papers shown
1.
Rudy, Samuel, et al.. (2024). Improving predictions of vortex induced vibrations via generalizable hydrodynamic databases across several current incidence angles. Journal of Fluids and Structures. 126. 104086–104086.
2.
Rudy, Samuel, et al.. (2023). Physics-based Data-informed Prediction of Vertical, Catenary, and Stepped Riser Vortex-induced Vibrations. International Journal of Offshore and Polar Engineering. 33(4). 367–379.
3.
Rudy, Samuel & Themistoklis P. Sapsis. (2022). Prediction of Intermittent Fluctuations from Surface Pressure Measurements on a Turbulent Airfoil. AIAA Journal. 60(7). 4174–4190. 8 indexed citations
4.
Rudy, Samuel, et al.. (2022). Optimized parametric hydrodynamic databases provide accurate response predictions and describe the physics of vortex-induced vibrations. Journal of Fluids and Structures. 112. 103607–103607. 4 indexed citations
5.
Rudy, Samuel, et al.. (2022). Data-driven prediction and study of vortex induced vibrations by leveraging hydrodynamic coefficient databases learned from sparse sensors. Ocean Engineering. 266. 112833–112833. 12 indexed citations
6.
Rudy, Samuel & Themistoklis P. Sapsis. (2022). Output-weighted and relative entropy loss functions for deep learning precursors of extreme events. Physica D Nonlinear Phenomena. 443. 133570–133570. 8 indexed citations
7.
Rudy, Samuel & Themistoklis P. Sapsis. (2021). Sparse methods for automatic relevance determination. Physica D Nonlinear Phenomena. 418. 132843–132843. 11 indexed citations
8.
Rudy, Samuel, et al.. (2021). Learning Optimal Parametric Hydrodynamic Database for Vortex-Induced Crossflow Vibration Prediction of Both Freely-Mounted Rigid and Flexible Cylinders. 2 indexed citations
9.
Kharazmi, Ehsan, Zhi‐Cheng Wang, Dixia Fan, et al.. (2021). From Data to Assessment Models, Demonstrated through a Digital Twin of Marine Risers. Offshore Technology Conference. 10 indexed citations
10.
Rudy, Samuel, Alessandro Alla, Steven L. Brunton, & J. Nathan Kutz. (2019). Data-driven identification of parametric partial differential equations. IRIS Research product catalog (Sapienza University of Rome). 190 indexed citations
11.
Rudy, Samuel, J. Nathan Kutz, & Steven L. Brunton. (2019). Deep learning of dynamics and signal-noise decomposition with time-stepping constraints. Journal of Computational Physics. 396. 483–506. 111 indexed citations
12.
Rudy, Samuel, Steven L. Brunton, & J. Nathan Kutz. (2019). Smoothing and parameter estimation by soft-adherence to governing equations. Journal of Computational Physics. 398. 108860–108860. 8 indexed citations
13.
Rudy, Samuel, et al.. (2018). Deep learning of dynamics and signal-noise decomposition with time-stepping constraints. arXiv (Cornell University). 2 indexed citations
14.
Kutz, J. Nathan, Samuel Rudy, Alessandro Alla, & Steven L. Brunton. (2017). Data-Driven discovery of governing physical laws and their parametric dependencies in engineering, physics and biology. IRIS Research product catalog (Sapienza University of Rome). 1–5. 7 indexed citations
15.
Rudy, Samuel, Steven L. Brunton, Joshua L. Proctor, & J. Nathan Kutz. (2017). Data-driven discovery of partial differential equations. Science Advances. 3(4). e1602614–e1602614. 931 indexed citations breakdown →
16.
17.
Rudy, Samuel. (2016). Data-driven discovery of partial differential equations. arXiv (Cornell University). 2 indexed citations

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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