Marco Tezzele

899 total citations
20 papers, 353 citations indexed

About

Marco Tezzele is a scholar working on Statistical and Nonlinear Physics, Statistics, Probability and Uncertainty and Computational Mechanics. According to data from OpenAlex, Marco Tezzele has authored 20 papers receiving a total of 353 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Statistical and Nonlinear Physics, 8 papers in Statistics, Probability and Uncertainty and 5 papers in Computational Mechanics. Recurrent topics in Marco Tezzele's work include Model Reduction and Neural Networks (16 papers), Probabilistic and Robust Engineering Design (8 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). Marco Tezzele is often cited by papers focused on Model Reduction and Neural Networks (16 papers), Probabilistic and Robust Engineering Design (8 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). Marco Tezzele collaborates with scholars based in Italy, United States and Germany. Marco Tezzele's co-authors include Gianluigi Rozza, Nicola Demo, Andrea Mola, Andrea Manzoni, Stefano Mariani, Karen Willcox, Giovanni Stabile, Francesco Ballarin, Dimitri Breda and Ilya Kolmanovsky and has published in prestigious journals such as Computer Methods in Applied Mechanics and Engineering, International Journal for Numerical Methods in Engineering and SIAM Journal on Scientific Computing.

In The Last Decade

Marco Tezzele

19 papers receiving 335 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marco Tezzele Italy 11 166 97 77 60 54 20 353
Zaoxu Zhu China 6 97 0.6× 112 1.2× 73 0.9× 50 0.8× 94 1.7× 10 332
Elizabeth Qian United States 7 215 1.3× 108 1.1× 98 1.3× 14 0.2× 96 1.8× 10 378
E. Andrés Spain 11 115 0.7× 146 1.5× 135 1.8× 57 0.9× 118 2.2× 28 604
Laura Mainini Italy 12 204 1.2× 117 1.2× 168 2.2× 97 1.6× 84 1.6× 36 560
Nicola Demo Italy 11 207 1.2× 118 1.2× 80 1.0× 29 0.5× 71 1.3× 22 336
Mohammad Khalil United States 15 75 0.5× 131 1.4× 185 2.4× 97 1.6× 61 1.1× 45 472
Luca Bonfiglio United States 12 45 0.3× 188 1.9× 57 0.7× 74 1.2× 73 1.4× 30 405
Tingwei Ji China 11 224 1.3× 313 3.2× 80 1.0× 61 1.0× 216 4.0× 32 569
Rohit Tripathy United States 5 243 1.5× 89 0.9× 251 3.3× 80 1.3× 47 0.9× 7 584
Mathieu Couplet France 8 245 1.5× 216 2.2× 213 2.8× 39 0.7× 119 2.2× 13 492

Countries citing papers authored by Marco Tezzele

Since Specialization
Citations

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

Fields of papers citing papers by Marco Tezzele

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marco Tezzele

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Tezzele. A scholar is included among the top collaborators of Marco Tezzele 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 Marco Tezzele. Marco Tezzele 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.
Kapteyn, Michael G., et al.. (2025). Digital-Twin-Enabled Multi-Spacecraft On-Orbit Operations. 1 indexed citations
2.
Tezzele, Marco, et al.. (2025). Non-intrusive reduced-order modeling for dynamical systems with spatially localized features. Computer Methods in Applied Mechanics and Engineering. 444. 118115–118115.
3.
Demo, Nicola, et al.. (2024). Data-driven discovery of delay differential equations with discrete delays. Journal of Computational and Applied Mathematics. 461. 116439–116439. 1 indexed citations
4.
Tezzele, Marco, et al.. (2024). A Local Approach to Parameter Space Reduction for Regression and Classification Tasks. Journal of Scientific Computing. 99(3). 2 indexed citations
5.
Demo, Nicola, Marco Tezzele, & Gianluigi Rozza. (2023). A DeepONet multi-fidelity approach for residual learning in reduced order modeling. Advanced Modeling and Simulation in Engineering Sciences. 10(1). 14 indexed citations
6.
Tezzele, Marco, et al.. (2023). A digital twin framework for civil engineering structures. Computer Methods in Applied Mechanics and Engineering. 418. 116584–116584. 81 indexed citations
7.
Tezzele, Marco, et al.. (2023). Multi‐fidelity data fusion through parameter space reduction with applications to automotive engineering. International Journal for Numerical Methods in Engineering. 124(23). 5293–5311. 6 indexed citations
8.
Tezzele, Marco, et al.. (2022). Kernel‐based active subspaces with application to computational fluid dynamics parametric problems using the discontinuous Galerkin method. International Journal for Numerical Methods in Engineering. 123(23). 6000–6027. 7 indexed citations
9.
Tezzele, Marco, et al.. (2022). A multifidelity approach coupling parameter space reduction and nonintrusive POD with application to structural optimization of passenger ship hulls. International Journal for Numerical Methods in Engineering. 124(5). 1193–1210. 11 indexed citations
10.
11.
Demo, Nicola, Marco Tezzele, & Gianluigi Rozza. (2021). A Supervised Learning Approach Involving Active Subspaces for an Efficient Genetic Algorithm in High-Dimensional Optimization Problems. SIAM Journal on Scientific Computing. 43(3). B831–B853. 15 indexed citations
12.
Tezzele, Marco, Nicola Demo, Andrea Mola, & Gianluigi Rozza. (2020). PyGeM: Python Geometrical Morphing. Software Impacts. 7. 100047–100047. 22 indexed citations
13.
Tezzele, Marco, et al.. (2020). On the comparison of LES data-driven reduced order approaches for hydroacoustic analysis. Computers & Fluids. 216. 104819–104819. 21 indexed citations
14.
Tezzele, Marco, Nicola Demo, Giovanni Stabile, Andrea Mola, & Gianluigi Rozza. (2020). Enhancing CFD predictions in shape design problems by model and parameter space reduction. Advanced Modeling and Simulation in Engineering Sciences. 7(1). 19 indexed citations
15.
Demo, Nicola, Marco Tezzele, & Gianluigi Rozza. (2019). A non-intrusive approach for the reconstruction of POD modal coefficients through active subspaces. Comptes Rendus Mécanique. 347(11). 873–881. 30 indexed citations
16.
Tezzele, Marco, et al.. (2019). BladeX: Python Blade Morphing. The Journal of Open Source Software. 4(34). 1203–1203. 2 indexed citations
17.
Demo, Nicola, Marco Tezzele, Andrea Mola, & Gianluigi Rozza. (2019). A complete data-driven framework for the efficient solution of parametric shape design and optimisation in naval engineering problems. UPCommons institutional repository (Universitat Politècnica de Catalunya). 111–121. 4 indexed citations
18.
Demo, Nicola, Marco Tezzele, & Gianluigi Rozza. (2018). EZyRB: Easy Reduced Basis method. The Journal of Open Source Software. 3(24). 661–661. 27 indexed citations
19.
Demo, Nicola, Marco Tezzele, & Gianluigi Rozza. (2018). PyDMD: Python Dynamic Mode Decomposition. The Journal of Open Source Software. 3(22). 530–530. 71 indexed citations
20.
Ballarin, Francesco, et al.. (2016). ADVANCES IN GEOMETRICAL PARAMETRIZATION AND REDUCED ORDER MODELS AND METHODS FOR COMPUTATIONAL FLUID DYNAMICS PROBLEMS IN APPLIED SCIENCES AND ENGINEERING: OVERVIEW AND PERSPECTIVES. IRIS Research product catalog (Sapienza University of Rome). 1013–1031. 17 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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