Eric C. Cyr

1.1k total citations
42 papers, 683 citations indexed

About

Eric C. Cyr is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics and Computational Theory and Mathematics. According to data from OpenAlex, Eric C. Cyr has authored 42 papers receiving a total of 683 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computational Mechanics, 13 papers in Statistical and Nonlinear Physics and 10 papers in Computational Theory and Mathematics. Recurrent topics in Eric C. Cyr's work include Advanced Numerical Methods in Computational Mathematics (18 papers), Model Reduction and Neural Networks (12 papers) and Computational Fluid Dynamics and Aerodynamics (7 papers). Eric C. Cyr is often cited by papers focused on Advanced Numerical Methods in Computational Mathematics (18 papers), Model Reduction and Neural Networks (12 papers) and Computational Fluid Dynamics and Aerodynamics (7 papers). Eric C. Cyr collaborates with scholars based in United States, United Kingdom and Canada. Eric C. Cyr's co-authors include John N. Shadid, Roger P. Pawlowski, Raymond S. Tuminaro, Nathaniel Trask, Mitchell Wood, Ravi G. Patel, Luis Chacòn, Stephen Bond, Myoungkyu Lee and Ignacio Tomaš and has published in prestigious journals such as Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering and Journal of Computational Chemistry.

In The Last Decade

Eric C. Cyr

41 papers receiving 653 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Eric C. Cyr United States 14 407 202 124 112 92 42 683
René Pinnau Germany 17 424 1.0× 99 0.5× 124 1.0× 98 0.9× 181 2.0× 77 861
Katharina Kormann Germany 11 328 0.8× 102 0.5× 92 0.7× 175 1.6× 92 1.0× 39 639
Chohong Min South Korea 17 897 2.2× 85 0.4× 152 1.2× 104 0.9× 74 0.8× 43 1.2k
James Willenbring United States 5 302 0.7× 47 0.2× 195 1.6× 119 1.1× 68 0.7× 14 782
Ch. Schwab Switzerland 19 586 1.4× 127 0.6× 282 2.3× 165 1.5× 209 2.3× 28 1.1k
S. A. Goreinov Russia 8 209 0.5× 85 0.4× 202 1.6× 86 0.8× 52 0.6× 10 549
Stefano Zampini Saudi Arabia 18 502 1.2× 65 0.3× 253 2.0× 189 1.7× 74 0.8× 33 883
Maxime Barrault France 4 478 1.2× 788 3.9× 122 1.0× 102 0.9× 189 2.1× 5 1.0k
Н. Л. Замарашкин Russia 9 214 0.5× 76 0.4× 289 2.3× 77 0.7× 61 0.7× 33 655
Veselin Dobrev United States 15 697 1.7× 44 0.2× 188 1.5× 128 1.1× 120 1.3× 29 1.0k

Countries citing papers authored by Eric C. Cyr

Since Specialization
Citations

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

Fields of papers citing papers by Eric C. Cyr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric C. Cyr. 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 Eric C. Cyr. The network helps show where Eric C. Cyr may publish in the future.

Co-authorship network of co-authors of Eric C. Cyr

This figure shows the co-authorship network connecting the top 25 collaborators of Eric C. Cyr. A scholar is included among the top collaborators of Eric C. Cyr 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 Eric C. Cyr. Eric C. Cyr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cyr, Eric C., et al.. (2025). Graph Neural Networks and Applied Linear Algebra. SIAM Review. 67(1). 141–175. 1 indexed citations
2.
Cyr, Eric C., et al.. (2024). Reduced basis approximations of parameterized dynamical partial differential equations via neural networks. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 7(1). 338–362.
3.
Bond, Stephen, et al.. (2023). An implicit-in-time DPG formulation of the 1D1V Vlasov-Poisson equations. Computers & Mathematics with Applications. 154. 103–119. 1 indexed citations
4.
Cartwright, Keith, et al.. (2022). Numerical simulation of a relativistic magnetron using a fluid electron model. Physics of Plasmas. 29(8). 1 indexed citations
5.
Cyr, Eric C., et al.. (2022). A monolithic algebraic multigrid framework for multiphysics applications with examples from resistive MHD. ETNA - Electronic Transactions on Numerical Analysis. 55. 365–390. 2 indexed citations
6.
Patel, Ravi G., Nathaniel Trask, Mitchell Wood, et al.. (2021). Thermodynamically consistent physics-informed neural networks for hyperbolic systems.. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 4 indexed citations
7.
Humphreys, David, Mark D. Boyer, J.M. Canik, et al.. (2020). Advancing Fusion with Machine Learning Research Needs Workshop Report. Journal of Fusion Energy. 39(4). 123–155. 22 indexed citations
8.
Shadid, John N., et al.. (2018). Scalable Preconditioners for Structure Preserving Discretizations of Maxwell Equations in First Order Form. SIAM Journal on Scientific Computing. 40(3). B723–B742. 6 indexed citations
9.
Lin, Paul, John N. Shadid, Jonathan Joseph Hu, Roger P. Pawlowski, & Eric C. Cyr. (2017). Performance of fully-coupled algebraic multigrid preconditioners for large-scale VMS resistive MHD. Journal of Computational and Applied Mathematics. 344. 782–793. 14 indexed citations
10.
Shadid, John N., et al.. (2016). Block Preconditioners for Stable Mixed Nodal and Edge finite element Representations of Incompressible Resistive MHD. SIAM Journal on Scientific Computing. 38(6). B1009–B1031. 33 indexed citations
11.
Lin, Paul, Stefan P. Domino, Travis C. Fisher, et al.. (2014). Towards Extreme-Scale Simulations with Next-Generation Trilinos: A Low Mach Fluid Application Case Study. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1485–1494. 7 indexed citations
12.
Elman, Howard C., et al.. (2014). A Block Preconditioner for an Exact Penalty Formulation for Stationary MHD. SIAM Journal on Scientific Computing. 36(6). B930–B951. 28 indexed citations
13.
Cyr, Eric C., John N. Shadid, & Timothy Wildey. (2014). Towards efficient backward-in-time adjoint computations using data compression techniques. Computer Methods in Applied Mechanics and Engineering. 288. 24–44. 13 indexed citations
14.
Cyr, Eric C., John N. Shadid, & Timothy Wildey. (2014). Approaches for Adjoint-Based A Posteriori Analysis of Stabilized Finite Element Methods. SIAM Journal on Scientific Computing. 36(2). A766–A791. 9 indexed citations
15.
Chaudhry, Jehanzeb H., Eric C. Cyr, Kuo Liu, et al.. (2014). Enhancing Least-Squares Finite Element Methods Through a Quantity-of-Interest. SIAM Journal on Numerical Analysis. 52(6). 3085–3105. 7 indexed citations
16.
Cyr, Eric C., John N. Shadid, Raymond S. Tuminaro, Roger P. Pawlowski, & Luis Chacòn. (2013). A New Approximate Block Factorization Preconditioner for Two-Dimensional Incompressible (Reduced) Resistive MHD. SIAM Journal on Scientific Computing. 35(3). B701–B730. 49 indexed citations
17.
Aksoylu, Burak, Stephen Bond, Eric C. Cyr, & Michael Holst. (2011). Goal-Oriented Adaptivity and Multilevel Preconditioning for the Poisson-Boltzmann Equation. Journal of Scientific Computing. 52(1). 202–225. 11 indexed citations
18.
Bond, Stephen, Jehanzeb H. Chaudhry, Eric C. Cyr, & Luke N. Olson. (2009). A first‐order system least‐squares finite element method for the Poisson‐Boltzmann equation. Journal of Computational Chemistry. 31(8). 1625–1635. 35 indexed citations
19.
Bond, Stephen & Eric C. Cyr. (2008). Numerical methods for computing the free energy of coarse-grained molecular systems. 2 indexed citations
20.
Giunta, Anthony, Laura Swiler, Shannon Brown, et al.. (2006). The Surfpack Software Library for Surrogate Modeling of Sparse Irregularly Spaced Multidimensional Data. 19 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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