Currently taught courses (A.Y 2025-2026)
- MATH-414: Stochastic simulation
- MATH-105(a): Advanced analysis II – vector analysis
- MATH-450: Numerical integration of stochastic differential equations
Courses taught in the past
- MATH-305: Introduction to Partial Differential Equations
- MATH-251(a/b/c/d): Numerical Analysis
- MATH-451: Numerical approximation of PDEs I
- MATH-472: Computational finance
- MATH-106(b): Analysis II
Doctoral courses and reading courses
- MATH-660: Numerical methods for data assimilation
- MATH-661: Numerical methods for random PDEs and uncertainty quantification
- MATH-631: Mathematical foundation of neural networks
- MATH-633: High Dimensional Approximation for PDEs with random parameters
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