Teaching

This page lists the courses I teach and my teaching materials.

ETH Zürich 2024 AI in the Sciences and Engineering Master’s course

Course catalogue page
YouTube lecture recordings: will be released soon
Course Moodle page (ETH students only)

ETH Zürich 2024 Projects in Machine Learning Research Master’s course

Course catalogue page
Lecture recording
Course Moodle page (ETH students only)

ETH Zürich 2023 Deep Learning in Scientific Computing Master’s course

Course catalogue page
YouTube lecture recordings
Code used in lectures
Tutorial exercises
Course Moodle page (ETH students only)

ETH Zürich 2023 Projects in Machine Learning Research Master’s course

Course catalogue page
Lecture recording
Course Moodle page (ETH students only)

Guest Lectures

• [2024] Introduction to physics-informed neural networks (mini-lecture). Imperial College London. [Slides] [Code]
• [2024] Scientific machine learning and physics-informed neural networks. Department of Engineering and Management Doctoral School Seminar Series, University of Padova. [Slides available soon]
• [2023] How to incorporate physical understanding into machine learning. Physical Society of Zurich. [Lecture recording]
• [2023] Guest lecturer for GAMM Juniors Summer School on Scientific Machine Learning.
• [2022] Scientific machine learning: ways to incorporate scientific principles into machine learning. University of Oxford / University of Wyoming / Lucerne University / Roche. [Slides]