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 offers for customers. Before that, I was a visiting graduate student at Harvard University, hosted by Issa Dahabreh in the CAUSALab.

I am broadly interested in reliable decision-making from multiple heterogeneous data sources. For example, leveraging AI models to combine randomized and observational evidence with the goal of improving efficiency and generalization.

My current research focuses on trial augmentation, a framework that improves the efficiency of clinical trials by safely incorporating external data through flexible AI models.