Teaching

Teaching for the Academic Year 2024-2025

• STOCHASTIC SIMULATION
• ADVANCED ANALYSIS II – VECTOR ANALYSIS
• NUMERICAL INTEGRATION OF STOCHASTIC DIFFERENTIAL EQUATIONS

Teaching for the Academic Year 2023-2024

• STOCHASTIC SIMULATION
• INTRODUCTION TO PARTIAL DIFFERENTIAL EQUATIONS
• NUMERICAL ANALYSIS

Teaching for the Academic Year 2022-2023

• ADVANCED ANALYSIS II
• STOCHASTIC SIMULATION
• INTRODUCTION TO PARTIAL DIFFERENTIAL EQUATION

Teaching for the Academic Year 2021-2022

• NUMERICAL ANALYSIS
• STOCHASTIC SIMULATION
• INTRODUCTION TO PARTIAL DIFFERENTIAL EQUATIONS

Teaching for the Academic Year 2020-2021

• ADVANCED ANALYSIS II
• STOCHASTIC SIMULATION
• INTRODUCTION TO PARTIAL DIFFERENTIAL EQUATIONS
• MATHEMATICAL FONDATIONS OF NEURAL NETWORKS

Teaching for the Academic Year 2019-2020

• STOCHASTIC SIMULATION
• INTRODUCTION TO PARTIAL DIFFERENTIAL EQUATIONS

Teaching for the Academic Year 2018-2019

• ADVANCED ANALYSIS II
• NUMERICAL APPROXIMATION OF PARTIAL DIFFERENTIAL EQUATIONS
• STOCHASTIC SIMULATION
  

Summer schools / other courses

• Mathematical and Algorithmic Aspects of Uncertainty Quantification (PhD course, Mathematical Models and Methods in Engineering , Politecnico di Milano, June 3-10, 2015)
• Numerical techniques for PDEs with random input data, by F. Nobile & R. Tempone. CIMPA School “Current trends in Computational methods for PDEs”, IISc, Bangalore, India, July 8-19, 2013