Tez profile

Marco Tezzele marco.tezzele@austin.utexas.edu | | | | |

Academic CV
I am a postdoctoral fellow in Karen Willcox's group at the Oden Institute, University of Texas at Austin. I work within the fields of applied mathematics, scientific machine learning, and digital twins. My research interests include the development of data-driven reduced order methods and parameter space reduction techniques. Currently, I am working on a NASA University Leadership Initiative project, developing a predictive digital twin of an autonomous drone used for cargo missions in an urban environment. This integrates reduced order modeling, uncertainty quantification, and real-world applications with economic and societal impacts.

In the last years, I developed of non-intrusive reduced order methods such as proper orthogonal decomposition with interpolation and dynamic mode decomposition, with applications in naval, nautical, biomedical, and automotive engineering. I created several scientific Python packages. I also coupled ROMs with reduction in parameter space using active subspaces (AS). I studied the effect of incorporating low-intrinsic dimensionality bias in a multi-fidelity setting to enhance regression and solution manifold reconstruction. I also extended AS developing kernel-based active subspaces and local active subspaces.

I received my Ph.D. in Mathematical Analysis, Modelling, and Applications at the International School of Advanced Studies (SISSA), Trieste, Italy, where I was part of the SISSA mathLab group, under the supervision of Gianluigi Rozza. My industrial Ph.D. grant was sponsored by Fincantieri S.p.A. (see the project here). The topic was the structural optimization of a passenger ship during the design step through parametric techniques and computational reduction.

News, Awards,
and Funding
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Check out my Medium profile!
  • [February 2024] Check out this piece on Digital Twins of civil engineering structured in the Oden Institute Newsletter!

  • [22-24 November 2023] Check out the posters presented at MORTech 2023 by two students I co-supervised:
    • Lorenzo Fabris (pdf): Structural optimization of cruise ships with non-intrusive parameter and model order reduction.
    • Matteo Torzoni (pdf): A computational framework for predictive digital twins of civil engineering structures. Winner of the Best Poster Award!

  • [21 August 2023] Find here my interview appeared in the newspapers Messaggero Veneto and Piccolo, in Italy.

  • [26 June 2023] Winner of the Anile-ECMI Prize for Mathematics in Industry. Ceremony held in Wroclaw, Poland, at ECMI 2023. Press release: Oden Institute, SISSA, Fincantieri SpA.

  • [9 June 2023] Invited speaker at the Department of Aeronautics and Astronautics, MIT. Host: Youssef Marzouk.

  • [22-26 May 2023] Invited speaker at the International Workshop on Reduced Order Methods, Institute for Mathematical Sciences, National University of Singapore.

  • [23 March 2023] Invited speaker at the University of Houston, Department of Mathematics. Host: Annalisa Quaini. Abstract.

  • [October 2022] Check out this profile article in the Oden Institute Newsletter!

  • [September 2022] Invited speaker at the Emory University, Department of Mathematics and Computer Science. Host: Alessandro Veneziani.

  • [11-15 July 2022] Invited speaker at the Summer School on Reduced Order Methods in Computational Fluid Dynamics, SISSA, Trieste, Italy.

  • [June 2022] Check out this article appeared in the ECCOMAS newletter, describing the major results of my PhD thesis.

  • [June 2022] Winner of one of the two ECCOMAS best PhD Thesis Awards in the field of Computational Methods in Applied Sciences and Engineering of 2021 (announcement). Ceremony held in Oslo, Norway, at ECCOMAS Congress 2022.

A digital twin framework for civil engineering structures [ bib | DOI | arXiv ]
Matteo Torzoni, Marco Tezzele, Stefano Mariani, Andrea Manzoni, Karen E. Willcox
Computer Methods in Applied Mechanics and Engineering, 418, 116584, 2024.

A multi-fidelity approach coupling parameter space reduction and non-intrusive POD with application to structural optimization of passenger ship hulls [ bib | DOI | arXiv ]
Marco Tezzele, Lorenzo Fabris, Matteo Sidari, Mauro Sicchiero, Gianluigi Rozza
International Journal for Numerical Methods in Engineering, 124(5):1193–1210, 2023.

A DeepONet multi-fidelity approach for residual learning in reduced order modeling [ bib | DOI | arXiv ]
Nicola Demo, Marco Tezzele, Gianluigi Rozza
Advanced Modeling and Simulation in Engineering Sciences 10, 12, 2023.

Multi-fidelity data fusion through parameter space reduction with applications to automotive engineering [ bib | DOI | arXiv ]
Francesco Romor, Marco Tezzele, Markus Mrosek, Carsten Othmer, Gianluigi Rozza
International Journal for Numerical Methods in Engineering, 124(23):5293-5311, 2023.

Student Mentoring
  • [2023-] Sebastian Henao-Garcia. PhD student at The University of Texas at Austin, TX, US.

  • [2023-] Leonidas Gkimisis. Visiting Ph.D. student, Max Planck Institute Magdeburg.

  • [2022-] Lorenzo Fabris. PhD student at SISSA, Trieste, Italy.

  • [2022-] Valentyn Visyn. PhD student at The University of Texas at Austin, TX, US.

  • [2022-2023] Matteo Torzoni. Visiting PhD student (6 months). Digital twins for monitoring of civil structures. Politecnico di Milano, Italy.

  • [2020-2021] Eleonora Donadini. Master Thesis: A data-driven approach for time-dependent optimal control problems by dynamic mode decomposition, University of Trieste, Italy.

  • [2019] Francesco Romor. Master Thesis: Reduction in Parameter Space for Problems approximated by Discontinuous-Galerkin Method in Computational Fluid Dynamics, University of Trieste, Italy.

  • [2018] Mahmoud Gadalla. Project: PRELICA - Advanced Methods for Hydro-Acoustic Design of Naval Propulsion, POR-FESR 2017, FVG, Italy.

  • [2018] Aurora Maurizio. Master in HPC Thesis: Representation of distribution networks of ships using graph-theory, SISSA & ICTP, Trieste, Italy.

  • [2018] Fabrizio Garotta. Master Thesis: Reduced Order Isogeometric Analysis approach for PDEs in parametrized domains, University of Pavia, Italy.

  • [2017] Nicola Demo. Project: Bulbous Bow Shape Optimization through Reduced Order Modelling, HEaD FSE, FVG, Italy.

PyDMD: Python Dynamic Mode Decomposition.
[ github | docs | DOI | arXiv ]

PyGeM: Python Geometrical Morphing.
[ github | docs | DOI ]

EZyRB: Easy Reduced Basis method.
[ github | docs | DOI ]

BladeX: Python Blade Morphing.
[ github | docs | DOI ]

ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis.
[ github | docs | DOI | Medium ]

Oden Institute for Computational Engineering and Sciences, UT Austin - Postdoctoral Fellow at Willcox Research Group - (2021-)

International School of Advanced Studies, SISSA - Assistant Researcher at SISSA mathLab - (2015-2018)

International School of Advanced Studies, SISSA - Ph.D. Mathematical Analysis, Modelling, and Applications financed by Fincantieri S.p.A. - (2018-2021)

ICTP & SISSA - Master in High Performance Computing - (2014-2015)

Technische Universität Kaiserslautern - ERASMUS Programme - (2012)

University of Milan - MSc Mathematics - (2010-2014)

University of Pavia - BSc Mathematics - (2006-2010)