I am a research assistant at Aarhus University 🇩🇰 in the Mechanics and Materials group. I am currently working on the application of Physics-Informed Machine Learning to the study of material stresses.
I graduated in Computational Science at EPFL 🇨🇭 and Mathematical Engineering at Polytechnic of Milan 🇮🇹.
When not working, I am passionate about mountaineering 🏔️, music 🎹 and cinematography 📽️.

Expertise

• Advanced mathematical analysis and modelling
• Numerical analysis for PDEs
• Machine Learning and Deep Learning
• Computational Fluid Dynamics
• Image Processing / Computer Vision
• Statistical Analysis
• High-performance, parallel and quantum computing

Author of libraries

• PIHNN
  

  Implementation and application of Physics-Informed Holomorphic Neural Networks (PIHNNs). Employed in a published article, the code is open-source under license LGPL 2.1.

• DUBeat
  

  High-order discontinuous Galerkin methods and applications to cardiac electrophysiology. Developed with Federica Botta, employed in a preprint, the code is open-source under license LGPL 3.

Programming languages

Advanced knowledge:

• C++ (STL, MPI, deal.II, Eigen, …)
• Python (NumPy, SciPy, PyTorch, Pandas, …)
• MATLAB
• CUDA
• FreeFem++
• COMSOL
• FEniCS
• ANSYS Fluent
• R
• C
• Bash shell

Good knowledge:

• C#
• Java
• AMPL
• JavaScript
• SolidWorks

Other utilities:

• Git, GitHub, LaTeX, Microsoft Office, Anaconda, Jupyter Notebook, Google Colab, Docker, Doxygen, Visual Studio
• OS: Microsoft Windows, Linux