Presented “Interpretable and Efficient Counterfactual Generation with Disentangled Variational Autoencoders” at HLDM 2024
I presented “Interpretable and Efficient Counterfactual Generation with Disentangled Variational Autoencoders” at the HLDM workshop at ECML PKDD 2024.

I am a PhD candidate in Artificial Intelligence at the University of Pisa, and I work with the Structured Machine Learning Group at the University of Trento.
My research focuses on uncertainty quantification and reliable machine learning, with particular interests in probabilistic calibration, conformal prediction, and human-AI decision making. More broadly, I am interested in developing the next generation of uncertainty-aware, trustworthy and human-centric AI frameworks.
I am always happy to chat about research, possible collaborations or interesting ideas, so feel free to reach out.