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.

My research aims to enable trustworthy decision-making using foundation models in scientific and biomedical settings. I am broadly interested in how foundation models can be used in a principled and reliable way to support conclusions and decisions, particularly when deploying them beyond their training populations.

For example, my recent work on trial augmentation develops a statistical framework for improving the efficiency of clinical trials by safely incorporating external data through flexible foundation models.