teaching

Applied AI Course

Master in Data Management and Curation (MDMC)
Area Science Park & SISSA, Trieste, Italy

A hands-on, project-based course where students work in teams to develop comprehensive AI solutions for real-world data challenges. Students apply machine learning techniques to raw datasets while adhering to FAIR principles and open science methodologies.

Key Components:

• Project Development: Teams of 4-5 students tackle real-world datasets and implement end-to-end solutions from data curation to model deployment
• Technical Implementation: Python programming, machine learning model development, and data structure interface design
• FAIR & Open Science: All work is designed to be transparent, reproducible, and interoperable, following FAIR-by-design principles

Course Structure: 30 hours including dataset exploration, strategy development, iterative implementation with feedback sessions, and final project presentation

Datasets: Students work with diverse datasets including neuroscience data (Sensorium competition) and nanomaterials imaging (SEM images), enriching them with metadata and building visualization tools for efficient data navigation and exploration.

More information: MDMC Program

Topological Data Analysis for Cosmology

Campagna School of Basic Science 2026 — Advanced Methods for the Physics of the Universe
Campagna (SA), Italy
31 August – 3 September 2026

Lecturer for a three-lecture course on topological data analysis and its application to cosmological data, given on 31 August, 2 September and 3 September 2026.

Topics Covered: Simplicial complexes and filtrations built from point clouds and scalar fields; persistent homology and the stability theorem; persistence diagrams and their vectorisations as summary statistics; use of topological summaries in cosmological parameter inference, including simulation-based inference; scope of applicability and limitations of the framework.

Context: The school is a joint initiative with the Korea Institute for Basic Science (IBS), under the patronage of the Department of Physics and Astronomy “Galileo Galilei” of the University of Padova. The 2026 edition comprised four courses: Inflationary Cosmology (R. Brandenberger), Cosmological Observables (P. Benincasa), Amplitude Methods for Gravitational Waves (C. Heissenberg), and Topological Data Analysis for Cosmology.

School website: CSBS 2026

Theoretical Aspects of Astroparticle Physics, Cosmology and Gravitation

PhD School - Exercise Sessions on Inflation
Galileo Galilei Institute, Florence, Italy
March 2025

Instructor for exercise sessions accompanying lectures on inflationary cosmology by Prof. Antonio Riotto at the annual GGI doctoral school. The school provides rigorous introductions to theoretical concepts and computational tools in astroparticle physics, cosmology, and gravitation.

Topics Covered: Inflation theory, gravitational waves, neutrino physics, dark matter searches, and cosmic ray physics through lectures complemented by hands-on computational sessions and discussion periods.

Role: Led exercise sessions and office hours helping students apply theoretical concepts to practical problems in inflationary cosmology.

School website: GGI School 2025