Alessandro Favero

I’m a final-year PhD student at EPFL in Switzerland, working with Matthieu Wyart and Pascal Frossard. This fall, I will join the University of Cambridge as a Research Associate and Physics-AI Fellow.
My research aims to deepen the scientific understanding of AI and deep learning, often drawing on methods from statistical physics. I am currently focused on generative models – in particular, continuous and discrete diffusion models – and the science of post-training, including large-scale model editing and merging.
Previously, I interned as an Applied Scientist in the Fundamental Research team at Amazon’s AWS AI Labs in the Bay Area, and completed my studies in theoretical physics at Sorbonne, Politecnico di Torino, SISSA, and ICTP.
news
Apr 08, 2025 | Talk on compositionality in diffusion models at the Theory+AI event, Perimeter Institute. |
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selected publications
- How compositional generalization and creativity improve as diffusion models are trainedInternational Conference on Machine Learning (ICML), PMLR, 2025
- A phase transition in diffusion models reveals the hierarchical nature of dataProceedings of the National Academy of Sciences (PNAS), 2025
- Multi-modal hallucination control by visual information groundingIEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024