Georg May

2.2k total citations · 1 hit paper
63 papers, 1.6k citations indexed

About

Georg May is a scholar working on Computational Mechanics, Numerical Analysis and Applied Mathematics. According to data from OpenAlex, Georg May has authored 63 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Computational Mechanics, 16 papers in Numerical Analysis and 7 papers in Applied Mathematics. Recurrent topics in Georg May's work include Advanced Numerical Methods in Computational Mathematics (50 papers), Computational Fluid Dynamics and Aerodynamics (47 papers) and Numerical methods for differential equations (14 papers). Georg May is often cited by papers focused on Advanced Numerical Methods in Computational Mathematics (50 papers), Computational Fluid Dynamics and Aerodynamics (47 papers) and Numerical methods for differential equations (14 papers). Georg May collaborates with scholars based in Germany, United States and Belgium. Georg May's co-authors include Antony Jameson, Z.J. Wang, Yen Liu, Aravind Balan, Ralf Hartmann, Per‐Olof Persson, Miguel R. Visbal, F. Bassi, Krzysztof Fidkowski and Andrew Cary and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Computational Physics and AIAA Journal.

In The Last Decade

Georg May

58 papers receiving 1.6k citations

Hit Papers

High‐order CFD methods: current status and perspective 2013 2026 2017 2021 2013 200 400 600
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. High‐order CFD methods: current status and perspective
    2013 683 citations Koen Hillewaert, Georg May et al. International Journal for Numerical Methods in Fluids profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Georg May Germany 17 1.5k 241 228 170 157 63 1.6k
S. G. Rubin United States 23 1.7k 1.2× 321 1.3× 278 1.2× 386 2.3× 56 0.4× 109 2.2k
Farzin Shakib United States 14 1.1k 0.8× 105 0.4× 180 0.8× 186 1.1× 97 0.6× 19 1.3k
Koen Hillewaert Belgium 17 1.3k 0.9× 165 0.7× 118 0.5× 394 2.3× 75 0.5× 58 1.5k
Harold Atkins United States 21 1.3k 0.9× 200 0.8× 168 0.7× 458 2.7× 223 1.4× 54 1.5k
Vladimir Gol’dshtein Israel 20 412 0.3× 439 1.8× 77 0.3× 192 1.1× 18 0.1× 103 1.1k
Andrea Crivellini Italy 16 1.1k 0.7× 65 0.3× 152 0.7× 229 1.3× 62 0.4× 60 1.2k
John J. H. Miller Ireland 20 946 0.6× 560 2.3× 2.4k 10.7× 34 0.2× 168 1.1× 90 2.9k
Philippe Geuzaine United States 13 1.1k 0.8× 65 0.3× 125 0.5× 333 2.0× 56 0.4× 26 1.3k
Sandro Manservisi Italy 21 1.4k 0.9× 93 0.4× 72 0.3× 206 1.2× 104 0.7× 94 1.6k
R. Camarero Canada 18 846 0.6× 130 0.5× 50 0.2× 170 1.0× 106 0.7× 110 1.1k

Countries citing papers authored by Georg May

Since Specialization
Citations

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

Fields of papers citing papers by Georg May

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Georg May

This figure shows the co-authorship network connecting the top 25 collaborators of Georg May. A scholar is included among the top collaborators of Georg May 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 Georg May. Georg May 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.
May, Georg, et al.. (2024). Conservative solution transfer between anisotropic meshes for time‐accurate hybridized discontinuous Galerkin methods. International Journal for Numerical Methods in Fluids. 96(6). 1011–1030.
2.
Hillewaert, Koen, et al.. (2024). Hybridized Discontinuous Galerkin Method for Multiphysics Problems: Application to Inductively Coupled Plasmas. Open Repository and Bibliography (University of Liège). 1 indexed citations
3.
4.
May, Georg, et al.. (2023). Metric-based anisotropic mesh adaptation for viscoelastic flows. Computers & Mathematics with Applications. 151. 67–79.
5.
Dolejší, Vít & Georg May. (2023). An Anisotropic hp-mesh Adaptation Method for Time-Dependent Problems Based on Interpolation Error Control. Journal of Scientific Computing. 95(2). 2 indexed citations
6.
May, Georg, et al.. (2023). A continuous hp-mesh model for discontinuous Petrov-Galerkin finite element schemes with optimal test functions. Computers & Mathematics with Applications. 147. 64–75.
7.
8.
Dolejší, Vít & Georg May. (2022). Anisotropic hp-Mesh Adaptation Methods. 5 indexed citations
9.
Balan, Aravind, et al.. (2021). A review and comparison of error estimators for anisotropic mesh adaptation for flow simulations. Computers & Fluids. 234. 105259–105259. 11 indexed citations
10.
May, Georg, et al.. (2021). An anisotropic h-adaptive strategy for discontinuous Petrov-Galerkin schemes using a continuous mesh model. Computers & Mathematics with Applications. 106. 1–17. 2 indexed citations
11.
May, Georg, et al.. (2020). Adjoint-based anisotropic hp-adaptation for discontinuous Galerkin methods using a continuous mesh model. Journal of Computational Physics. 409. 109321–109321. 13 indexed citations
12.
Dolejší, Vít, et al.. (2019). A goal-oriented anisotropic hp-mesh adaptation method for linear convection–diffusion–reaction problems. Computers & Mathematics with Applications. 78(9). 2973–2993. 8 indexed citations
13.
Dolejší, Vít, et al.. (2017). Anisotropic hp-mesh optimization technique based on the continuous mesh and error models. Computers & Mathematics with Applications. 74(1). 45–63. 8 indexed citations
14.
Dolejší, Vít, et al.. (2017). A continuous hp-mesh model for adaptive discontinuous Galerkin schemes. Applied Numerical Mathematics. 124. 1–21. 18 indexed citations
15.
Balan, Aravind, et al.. (2016). Adjoint-based hp -adaptivity on anisotropic meshes for high-order compressible flow simulations. Computers & Fluids. 139. 47–67. 23 indexed citations
16.
Schütz, Jochen, Sebastian Noelle, Christina Steiner, & Georg May. (2013). A Note on Adjoint Error Estimation for One-Dimensional Stationary Balance Laws with Shocks. SIAM Journal on Numerical Analysis. 51(1). 126–136.
17.
Balan, Aravind, Georg May, & Joachim Schöberl. (2011). A Stable Spectral Difference Method for Triangles. 49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition. 5 indexed citations
18.
19.
May, Georg & Antony Jameson. (2006). A Spectral Difference Method for the Euler and Navier-Stokes Equations on Unstructured Meshes. 44th AIAA Aerospace Sciences Meeting and Exhibit. 59 indexed citations
20.
May, Georg, Shihab Shamma, & Robert L. White. (1979). A tantalum-on-sapphire microelectrode array. IEEE Transactions on Electron Devices. 26(12). 1932–1939. 37 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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