Hello World,
I am Riccardo, an enthusiastic researcher (Ph.D.) at
Causal
Learning and Artificial Intelligence Lab (Vienna) advised by
Francesco Locatello and
and co-advised by Cordelia Schmid as a member of ELLIS Society.
Through my research, I aim to revisit general representation learning objectives
when interested in causal downstream tasks (e.g., Treatment Effect Estimation)
in order to (i) improve experiments' efficiency, and (ii) provide trustworthy
guarantees to AI-powered scientific discovery.
Aiming to impact in applied sciences, currently collaborating with experimental ecologists and neuroscientists.
Really interested in applications in public health and medicine as well.
I have previously conducted research on Causal Machine Learning at
Harvard University
(2022-2023) and EPFL
(2020-2022), worked as a Machine Learning Engineer in 3 different
internships (2 in industry, 1 in academia), and failed
postponed to launch my own start-up on Responsible AI (2023).
This is my personal website where you can go through my publications and accomplished projects publicly available. Enjoy your reading, and do not hesitate to reach out for any constructive discussion.
News
5 months visit to Cordelia Schmid at Willow group (Paris).
[New Paper] Causal Lifting of Neural Representations: Zero-Shot Generalization for Causal Inferences accepted at ICLR'25-XAI4Science Workshop (Singapore). The Area Chair: “[...] the contributions made in this paper are significant, bringing us a step closer towards using AI to investigate causal scientific questions”.
Unifying Causal Representation Learning with the Invariance Principle accepted at ICLR'25 (Singapore).
Presenting Smoke and Mirrors in Causal Downstream Tasks at NeurIPS'24 (Vancouver).
Running Florence Marathon in 2h42m35s. Looking for new challenges!
Selected in Nova 111 Student List among the 10 most promising Italian Computer Scientists Under25.