Piersilvio De Bartolomeis

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I am a PhD student in the Computer Science Department at ETH Zürich, advised by Fanny Yang, and part of the Institute for Machine Learning. I was previously an Applied Scientist Intern at Amazon Science in Seattle, where I worked on machine learning and experimentation to select the best product offers for customers. Before that, I was a visiting graduate student at Harvard University, hosted by Issa Dahabreh in the CAUSALab.

My current research focuses on trial augmentation - a new line of work that improves the efficiency of clinical trials by safely integrating external data and flexible machine learning models into trial design and analysis.

news

Aug 29, 2025 Our paper Robust integration of external control data in randomized trials has been accepted for publication in Biometrics. Even more exciting, it has been selected for a Discussion where leading experts will share their perspectives on our contribution.
Jul 4, 2025 Our workshop CauScien: Uncovering Causality in Science has been accepted at NeurIPS 2025!
May 9, 2025 I have been invited to present our paper Efficient Randomized Experiments Using Foundation Models at the American Statistical Association Covariate Adjustment Working Group, which brings together statisticians from both academia and pharma companies. The slides can be found here.