Matteo Parsani

1.2k total citations
69 papers, 758 citations indexed

About

Matteo Parsani is a scholar working on Computational Mechanics, Numerical Analysis and Applied Mathematics. According to data from OpenAlex, Matteo Parsani has authored 69 papers receiving a total of 758 indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Computational Mechanics, 14 papers in Numerical Analysis and 12 papers in Applied Mathematics. Recurrent topics in Matteo Parsani's work include Computational Fluid Dynamics and Aerodynamics (45 papers), Fluid Dynamics and Turbulent Flows (33 papers) and Advanced Numerical Methods in Computational Mathematics (22 papers). Matteo Parsani is often cited by papers focused on Computational Fluid Dynamics and Aerodynamics (45 papers), Fluid Dynamics and Turbulent Flows (33 papers) and Advanced Numerical Methods in Computational Mathematics (22 papers). Matteo Parsani collaborates with scholars based in Saudi Arabia, United States and Belgium. Matteo Parsani's co-authors include Mark H. Carpenter, Eric J. Nielsen, Lisandro Dalcín, David I. Ketcheson, Hua Shen, Chris Lacor, Hendrik Ranocha, Travis C. Fisher, Randall J. LeVeque and David C. Del Rey Fernández and has published in prestigious journals such as Journal of Fluid Mechanics, Scientific Reports and Journal of Computational Physics.

In The Last Decade

Matteo Parsani

62 papers receiving 727 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matteo Parsani Saudi Arabia 17 639 129 123 90 89 69 758
Nail K. Yamaleev United States 15 671 1.1× 193 1.5× 103 0.8× 184 2.0× 72 0.8× 42 767
Praveen Chandrashekar India 14 590 0.9× 231 1.8× 75 0.6× 58 0.6× 73 0.8× 46 700
Florian Hindenlang Germany 12 552 0.9× 108 0.8× 70 0.6× 98 1.1× 75 0.8× 29 663
Andrew R. Winters Germany 18 938 1.5× 203 1.6× 124 1.0× 56 0.6× 120 1.3× 33 1.1k
Huazhong Tang China 21 940 1.5× 332 2.6× 253 2.1× 67 0.7× 120 1.3× 61 1.2k
Bojan Popov United States 15 845 1.3× 268 2.1× 164 1.3× 41 0.5× 90 1.0× 53 969
Lilia Krivodonova Canada 11 1.1k 1.7× 229 1.8× 269 2.2× 72 0.8× 72 0.8× 24 1.1k
Christopher A. Kennedy United States 8 672 1.1× 68 0.5× 416 3.4× 79 0.9× 109 1.2× 9 917
Zhengfu Xu United States 16 550 0.9× 199 1.5× 159 1.3× 28 0.3× 40 0.4× 29 663
H. van der Ven Netherlands 13 742 1.2× 56 0.4× 169 1.4× 122 1.4× 61 0.7× 40 871

Countries citing papers authored by Matteo Parsani

Since Specialization
Citations

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

Fields of papers citing papers by Matteo Parsani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matteo Parsani

This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Parsani. A scholar is included among the top collaborators of Matteo Parsani 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 Matteo Parsani. Matteo Parsani 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.
Zanotti, Alex, et al.. (2025). Quasi-compact model for accurate noise prediction of complex rotor configurations. Applied Acoustics. 240. 110928–110928. 2 indexed citations
2.
Gao, Wei, et al.. (2025). Direct numerical simulation of particle-laden turbulent channel flow over superhydrophobic surfaces. Physics of Fluids. 37(3). 1 indexed citations
3.
Galimberti, Luca, Lisandro Dalcín, Saleh Rezaeiravesh, et al.. (2025). Effects of lower floating-point precision on scale-resolving numerical simulations of turbulence. Journal of Computational Physics. 549. 114600–114600.
4.
Jahdali, Rasha Al, et al.. (2024). Fully-Discrete Lyapunov Consistent Discretizations for Parabolic Reaction-Diffusion Equations with r Species. Communications on Applied Mathematics and Computation. 8(1). 195–231. 1 indexed citations
5.
Parsani, Matteo, et al.. (2024). A hybrid discrete exterior calculus and finite difference method for anelastic convection in spherical shells. Computers & Fluids. 277. 106280–106280. 1 indexed citations
6.
Schmidt, Oliver T., et al.. (2024). Unlocking massively parallel spectral proper orthogonal decompositions in the PySPOD package. Computer Physics Communications. 302. 109246–109246. 5 indexed citations
7.
Ranocha, Hendrik, et al.. (2023). On Error-Based Step Size Control for Discontinuous Galerkin Methods for Compressible Fluid Dynamics. Communications on Applied Mathematics and Computation. 7(1). 3–39. 7 indexed citations
8.
Parsani, Matteo, et al.. (2023). Impact of Evanescence Process on Three-Dimensional Sub-Diffusion-Based Molecular Communication Channel. IEEE Transactions on NanoBioscience. 22(4). 923–932. 2 indexed citations
9.
Parsani, Matteo, et al.. (2023). Mobile Sub-diffusion Molecular Communication Channel. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 12. 152–153.
10.
Dalcín, Lisandro, et al.. (2022). Eigenanalysis and non-modal analysis of collocated discontinuous Galerkin discretizations with the summation-by-parts property. Computers & Mathematics with Applications. 124. 196–217.
11.
Jahdali, Rasha Al, et al.. (2022). Evaluation of next-generation high-order compressible fluid dynamic solver on cloud computing for complex industrial flows. Array. 17. 100268–100268. 3 indexed citations
12.
Parsani, Matteo, et al.. (2021). Development and analysis of entropy stable no-slip wall boundary conditions for the Eulerian model for viscous and heat conducting compressible flows. Partial Differential Equations and Applications. 2(6). 6 indexed citations
13.
Parsani, Matteo, et al.. (2021). Triple Decomposition of Velocity Gradient Tensor in Compressible Turbulence. Fluids. 6(3). 98–98. 6 indexed citations
14.
Ranocha, Hendrik, Lisandro Dalcín, Matteo Parsani, & David I. Ketcheson. (2021). Optimized Runge-Kutta Methods with Automatic Step Size Control for Compressible Computational Fluid Dynamics. arXiv (Cornell University). 27 indexed citations
15.
Ketcheson, David I., et al.. (2020). RK-Opt: A package for the design of numerical ODE solvers. The Journal of Open Source Software. 5(54). 2514–2514. 7 indexed citations
16.
Ketcheson, David I., et al.. (2020). NodePy: A package for the analysis of numerical ODE solvers. The Journal of Open Source Software. 5(55). 2515–2515. 6 indexed citations
17.
Shen, Hua & Matteo Parsani. (2017). The role of multidimensional instabilities in direct initiation of gaseous detonations in free space. Journal of Fluid Mechanics. 813. 32 indexed citations
18.
Espath, Luis, et al.. (2017). An energy-stable generalized-α method for the Swift–Hohenberg equation. Journal of Computational and Applied Mathematics. 344. 836–851. 19 indexed citations
19.
Parsani, Matteo, David I. Ketcheson, & Willem Deconinck. (2013). Optimized Explicit Runge--Kutta Schemes for the Spectral Difference Method Applied to Wave Propagation Problems. SIAM Journal on Scientific Computing. 35(2). A957–A986. 25 indexed citations
20.
Abeele, Kris Van Den, Ghader Ghorbaniasl, Matteo Parsani, & Chris Lacor. (2008). A stability analysis for the spectral volume method on tetrahedral grids. Journal of Computational Physics. 228(2). 257–265. 15 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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