John Burkardt

2.0k total citations
38 papers, 1.4k citations indexed

About

John Burkardt is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics and Statistics, Probability and Uncertainty. According to data from OpenAlex, John Burkardt has authored 38 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computational Mechanics, 10 papers in Statistical and Nonlinear Physics and 10 papers in Statistics, Probability and Uncertainty. Recurrent topics in John Burkardt's work include Probabilistic and Robust Engineering Design (10 papers), Advanced Numerical Methods in Computational Mathematics (9 papers) and Model Reduction and Neural Networks (6 papers). John Burkardt is often cited by papers focused on Probabilistic and Robust Engineering Design (10 papers), Advanced Numerical Methods in Computational Mathematics (9 papers) and Model Reduction and Neural Networks (6 papers). John Burkardt collaborates with scholars based in United States, Canada and China. John Burkardt's co-authors include Max Gunzburger, Werner C. Rheinboldt, Michael Eldred, Hyung‐Chun Lee, Janet Peterson, Vicente Romero, Marcus R. Garvie, Mauro Perego, Clayton Webster and Hoa Nguyen and has published in prestigious journals such as Physical Review B, Journal of Hydrology and Computer Methods in Applied Mechanics and Engineering.

In The Last Decade

John Burkardt

38 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John Burkardt United States 20 433 409 335 318 223 38 1.4k
Eric Phipps United States 15 449 1.0× 341 0.8× 197 0.6× 326 1.0× 109 0.5× 43 1.2k
Tan Bui–Thanh United States 20 806 1.9× 692 1.7× 965 2.9× 255 0.8× 194 0.9× 58 2.0k
Akil Narayan United States 19 230 0.5× 562 1.4× 302 0.9× 236 0.7× 63 0.3× 90 1.1k
Clayton Webster United States 16 500 1.2× 1.3k 3.2× 396 1.2× 539 1.7× 142 0.6× 45 1.8k
Jeff Borggaard United States 24 1.3k 3.1× 656 1.6× 983 2.9× 215 0.7× 190 0.9× 127 2.0k
Matthias Heinkenschloss United States 26 837 1.9× 277 0.7× 391 1.2× 704 2.2× 625 2.8× 75 1.8k
Bart van Bloemen Waanders United States 14 234 0.5× 213 0.5× 298 0.9× 127 0.4× 94 0.4× 47 834
Mario Ohlberger Germany 24 1.4k 3.3× 297 0.7× 738 2.2× 569 1.8× 385 1.7× 82 2.3k
Karen Veroy Germany 14 738 1.7× 457 1.1× 1.0k 3.1× 115 0.4× 258 1.2× 49 1.3k
Zhu Wang United States 23 931 2.2× 356 0.9× 884 2.6× 126 0.4× 226 1.0× 91 1.5k

Countries citing papers authored by John Burkardt

Since Specialization
Citations

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

Fields of papers citing papers by John Burkardt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Burkardt

This figure shows the co-authorship network connecting the top 25 collaborators of John Burkardt. A scholar is included among the top collaborators of John Burkardt 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 John Burkardt. John Burkardt 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.
Burkardt, John & Marcus R. Garvie. (2023). An integer linear programming approach to solving the Eternity Puzzle. Theoretical Computer Science. 975. 114138–114138. 1 indexed citations
2.
Burkardt, John, Yixuan Wu, & Yanzhi Zhang. (2021). A Unified Meshfree Pseudospectral Method for Solving Both Classical and Fractional PDEs. SIAM Journal on Scientific Computing. 43(2). A1389–A1411. 21 indexed citations
3.
Garvie, Marcus R. & John Burkardt. (2020). A new mathematical model for tiling finite regions of the plane with polyominoes. Contributions to Discrete Mathematics. 15(2). 95–131. 4 indexed citations
4.
Burkardt, John & Cătălin Trenchea. (2020). Refactorization of the midpoint rule. Applied Mathematics Letters. 107. 106438–106438. 13 indexed citations
5.
Burkardt, John. (2017). Finite Elements for the (Navier) Stokes Equations. Figshare. 2 indexed citations
6.
Xu, Feifei, Max Gunzburger, & John Burkardt. (2016). A multiscale method for nonlocal mechanics and diffusion and for the approximation of discontinuous functions. Computer Methods in Applied Mechanics and Engineering. 307. 117–143. 21 indexed citations
7.
Xu, Feifei, Max Gunzburger, John Burkardt, & Qiang Du. (2016). A Multiscale Implementation Based on Adaptive Mesh Refinement for the Nonlocal Peridynamics Model in One Dimension. Multiscale Modeling and Simulation. 14(1). 398–429. 13 indexed citations
8.
Garvie, Marcus R., John Burkardt, & Jeffrey R. Morgan. (2015). Simple Finite Element Methods for Approximating Predator–Prey Dynamics in Two Dimensions Using Matlab. Bulletin of Mathematical Biology. 77(3). 548–578. 28 indexed citations
9.
Zhang, Guannan, Clayton Webster, Max Gunzburger, & John Burkardt. (2015). A Hyperspherical Adaptive Sparse-Grid Method for High-Dimensional Discontinuity Detection. SIAM Journal on Numerical Analysis. 53(3). 1508–1536. 5 indexed citations
10.
Jacobsen, Doug, Max Gunzburger, Todd D. Ringler, John Burkardt, & Janet Peterson. (2013). Parallel algorithms for planar and spherical Delaunay construction with an application to centroidal Voronoi tessellations. Geoscientific model development. 6(4). 1353–1365. 29 indexed citations
11.
Perego, Mauro, Max Gunzburger, & John Burkardt. (2012). Parallel finite-element implementation for higher-order ice-sheet models. Journal of Glaciology. 58(207). 76–88. 37 indexed citations
12.
Stoyanov, Miroslav, Max Gunzburger, & John Burkardt. (2011). PINK NOISE, 1/fαNOISE, AND THEIR EFFECT ON SOLUTIONS OF DIFFERENTIAL EQUATIONS. International Journal for Uncertainty Quantification. 1(3). 257–278. 20 indexed citations
13.
Burkardt, John. (2009). MATLAB Parallel Computing. 2 indexed citations
14.
Nguyen, Hoa, et al.. (2008). Constrained CVT meshes and a comparison of triangular mesh generators. Computational Geometry. 42(1). 1–19. 32 indexed citations
15.
Burkardt, John, Max Gunzburger, & Clayton Webster. (2007). REDUCED ORDER MODELING OF SOME NONLINEAR STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS. 20 indexed citations
16.
Kim, Sang‐Bum, John Burkardt, Max Gunzburger, Janet Peterson, & Chia-Ren Hu. (2007). Effects of sample geometry on the dynamics and configurations of vortices in mesoscopic superconductors. Physical Review B. 76(2). 10 indexed citations
17.
Burkardt, John, Max Gunzburger, & Janet Peterson. (2002). Insensitive Functionals, Inconsistent Gradients, Spurious Minima, and Regularized Functionals in Flow Optimization Problems. International journal of computational fluid dynamics. 16(3). 171–185. 25 indexed citations
18.
Rheinboldt, Werner C. & John Burkardt. (1983). Algorithm 596. ACM Transactions on Mathematical Software. 9(2). 236–241. 84 indexed citations
19.
Rheinboldt, Werner C. & John Burkardt. (1983). ALGORITHM 596 A Program for a Locally Parameterized Continuation Process. 38 indexed citations
20.
Rheinboldt, Werner C. & John Burkardt. (1981). A Program for a Locally-Parametrized Continuation Process.. Defense Technical Information Center (DTIC). 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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