Francesco Regazzoni

Francesco Regazzoni

Associate Professor in Numerical Analysis

MOX, Dep. of Mathematics, Politecnico di Milano

Research interests

Cardiac modeling

Cardiac modeling

The human heart is a sophisticated machine, finely tuned…

Numerical Approximation of PDEs

Numerical Approximation of PDEs

I am interested in the development of methods for the…

Scientific Machine Learning

Scientific Machine Learning

Scientific Machine Learning creates concrete bridges and…

Honors and Awards

deal.II
Best paper based on deal.II of the year 2023, for the paper “A comprehensive and biophysically detailed computational model of the whole human heart electromechanics” by M. Fedele, R. Piersanti, F. Regazzoni, M. Salvador, P. C. Africa, M. Bucelli, A. Zingaro, L. Dede’, A. Quarteroni.
SIMAI - Italian Society of Applied and Industrial Mathematics
Prize awarded by SIMAI (Italian Society of Applied and Industrial Mathematics) to young researchers (up to 35 years old) based on: autonomy in the scientific production; capability of developing lines of research of interest to applications of mathematics; international recognition; participation to projects relevant to Industrial Mathematics. The award consists of a money prize and a personal invitation to present the research work in one of the next meetings organized by SIMAI.
CMAME - Computer Methods in Applied Mechanics and Engineering
Best paper published in CMAME (Computer Methods in Applied Mechanics and Engineering) in the years 2022-2023, for the paper “A comprehensive and biophysically detailed computational model of the whole human heart electromechanics” by M. Fedele, R. Piersanti, F. Regazzoni, M. Salvador, P. C. Africa, M. Bucelli, A. Zingaro, L. Dede’, A. Quarteroni.
EMS - European Mathematical Society
Nominated member of the EMS Young Academy (EMYA), established by the European Mathematical Society (EMS) with the aim of strengthening the role of the mathematical community and the perspective of the generation of young mathematicians in Europe.
CMBE - Computational and Mathematical Biomedical Engineering
Prize awarded for the best PhD Thesis related to Biomedical Engineering defended in 2020, 2021 or 2022. The award consists of a registration fee waiver, a travel grant and a money prize, sponsored by the International Journal for Numerical Methods in Biomedical Engineering (IJNMBE).
ECCOMAS - European Community on Computational Methods in Applied Sciences
Prize awarded by ECCOMAS, the European Community on Computational Methods in Applied Sciences, for the best PhD Thesis in the field of Computational Methods in Applied Sciences and Engineering. The award is accompanied with a money prize and the winner awarded during the 8th ECCOMAS Congress (Oslo, Norway).
VPHi - Virtual Physiological Human Institute
Prize awarded by VPH Institute to reward individuals for outstanding achievements during their PhD thesis. The award is accompanied with a money prize and the winner is invited to give a plenary lecture at the 5th VPH Barcelona Summer School.
AIMETA - Italian Association of Theoretical and Applied Mechanics
Prize awarded by AIMETA (Italian Association of Theoretical and Applied Mechanics, Biomechanics Group - GBMA) for the best Doctoral Thesis on Theoretical and Applied Biomechanics, defended in the period May 1st, 2019 - April 30th, 2020 in an Italian University or Research Centre.
Virtual Physiological Human Congress
Best talk in the conference VPH2020 among young researchers (PhD defended in 2016 and later). Voted by the Scientific Committee members.
Politecnico di Milano
Carlo Cercignani Prize
Politecnico di Milano Oct 2017
Best thesis of the year 2016 in Mathematical Engineering - Computational Science and Engineering (Politecnico di Milano).

Publications

See the full list of publications.

Teaching

The teaching material is available on WeBeeP.

PhD courses

2023-2024 Lecturer. Foundations and Applications of Machine Learning in Scientific Computing (Politecnico di Torino)
2025-2026 Lecturer (with Prof. Paolo Lella). Analytic and topological aspects in Scientific Machine Learning (Politecnico di Milano)

MSc courses

2025-2026 Teach. Ass. Numerical Analysis for PDEs (Mathematical Eng., PoliMi)
2025-2026 Lecturer. Comp. Methods and Machine Learning for Eng. Modeling (Building Eng., PoliMi)
2024-2025 Teach. Ass. Numerical Analysis for PDEs (Mathematical Eng., PoliMi)
2024-2025 Lecturer. Computational Methods for Building Eng. (Building Eng., PoliMi)
2023-2024 Teach. Ass. Numerical Analysis for PDEs (Mathematical Eng., PoliMi)
2022-2023 Teach. Ass. Numerical Analysis for PDEs (Mathematical Eng., PoliMi)
2022-2023 Teach. Ass. Numerical Analysis for Machine Learning (Mathematical Eng., PoliMi)
2021-2022 Teach. Ass. Numerical Analysis for PDEs (Mathematical Eng., PoliMi)
2021-2022 Tutor. Numerical Analysis for PDEs (Mathematical Eng., PoliMi)
2021-2022 Teach. Ass. Numerical Analysis for Machine Learning (Mathematical Eng., PoliMi)
2020-2021 Teach. Ass. Numerical Analysis for PDEs (Mathematical Eng., PoliMi)
2020-2021 Tutor. Numerical Analysis for PDEs (Mathematical Eng., PoliMi)
2020-2021 Teach. Ass. Numerical Analysis for Machine Learning (Mathematical Eng., PoliMi)
2019-2020 Teach. Ass. Numerical Analysis for PDEs (Mathematical Eng., PoliMi)
2019-2020 Tutor. Numerical Analysis for PDEs (Mathematical Eng., PoliMi)
2018-2019 Tutor. Numerical Analysis for PDEs (Mathematical Eng., PoliMi)
2017-2018 Teach. Ass. Numerical Methods for PDEs (Civil Eng., PoliMi)

BSc courses

2025-2026 Lecturer. Numerical Methods (Biomedical Eng., PoliMi)
2024-2025 Lecturer. Numerical Methods (Biomedical Eng., PoliMi)
2023-2024 Lecturer. Numerical Methods (Biomedical Eng., PoliMi)
2022-2023 Lecturer. Numerical Methods (Biomedical Eng., PoliMi)
2020-2021 Teach. Ass. Numerical Methods (Biomedical Eng., PoliMi)
2017-2018 Teach. Ass. Applied Numerical Analysis (Aerospace Eng., PoliMi)
2016-2017 Teach. Ass. Applied Numerical Analysis (Aerospace Eng., PoliMi)

Open Positions

If interested in any of the following positions, feel free to reach out.


Post-doc positions in Scientific Machine Learning

Logo FIS2

  • Funding: FIS Starting Grant (1.3 M€) SYNERGIZE: Synergizing Numerical Methods and Machine Learning for a new generation of computational models.

  • Research topic: Scientific Machine Learning is reshaping computational modeling in physics, engineering, and applied sciences. This research will develop novel methodologies to:

    • bridge Numerical Analysis and Machine Learning to develop reliable methods that seamlessly integrate physics with data while preserving theoretical soundness;
    • design efficient solvers for differential problems, significantly reducing computational costs and environmental impact;
    • enhance the reliability, interpretability, and applicability of Machine Learning in Scientific Computing.

  • Open Positions:

    • Post-doctoral positions: required a Ph.D. in Applied Mathematics or a related field, and a solid background in Computational Sciences or Scientific Machine Learning.

Ph.D. and Post-doc positions in Scientific Computing

Logo HeartCORE Logo ERC

  • Funding: ERC Advanced Grant (2.6 M€) HeartCORE: Boosting predictive concepts on arrhythmogenesis resolving and unifying cardiac electrophysiology and structural remodelling at organ-level.

  • Research topic: Development and implementation of computational models, with a particular emphasis on

    • the development of novel methods for solving inverse problems related to optical measurements;
    • the integration of high-resolution structural data into organ-level simulations of cardiac function.

  • Open positions:

    • Post-doctoral positions: required a Ph.D. in Applied Mathematics or Computational Modeling, a solid background in Computational Sciences and experience in cardiac applications.
    • Ph.D. opportunities: we also welcome highly motivated students interested in pursuing a Ph.D. in Mathematical Models and Methods with projects related to HeartCORE.

MSc theses

There are also several Master Thesis projects for students in Mathematics, Mathematical Engineering and Biomedical Engineering.

Contact

  • francesco.regazzoni (at) polimi.it
  • Via Bonardi 9, Milano, MI 20133
  • Building 14 (“Nave”), 5th floor