Hello World,
I am Riccardo, an enthusiastic researcher (Ph.D.) at Causal Learning and Artificial Intelligence Lab (Vienna) led by Francesco Locatello and and collaborating with Cordelia Schmid as a member of ELLIS Society. Through my research, I aim to bring (causal) scientific experiments into the modern ML era—scaling sample size, measurement complexity, and number of testable hypotheses, currently limited by analysis bottlenecks. On this matter, I have led the formulation and development of two complementary frameworks for modern treatment-effect estimation and discovery: (i) Prediction-Powered Causal Inference (PPCI), which leverages machine-learning predictions as surrogates for unobserved outcomes while mitigating the model bias; and (ii) Exploratory Causal Inference (ECI), which leverages high-dimensional measurements and interpretable representations to generate data-driven hypotheses at scale. I actively collaborate with biologists and neuroscientists to translate these methods into empirical findings, with an eye toward public health and medicine.

I have previously conducted research on Causal Machine Learning at Harvard University (2022-2023) and EPFL (2020-2022), worked as a machine-learning engineer/eesearcher in 3 different internships (2 in industry, 1 in academia), and failed postponed launching a startup on Responsible AI (2023).

This is my personal website where you can browse my publications and accomplished projects publicly available. Enjoy your reading, and do not hesitate to reach out for any constructive discussion.