I’m am postdoctoral researcher at Stanford University in the group of Prof. Jure Leskovec. Previously, I completed my PhD at ETH Zurich in the Machine Learning and Computational Biology Lab , and prior to that I obtained an MD at the University of Basel. Here, you can find my current academic CV.
During my PhD, I developed machine learning models for medical time series and developed methods for representation learning, spiked with topological data analysis. Since joining Stanford CS for my postdoc, I have been exploring novel frontiers of medical AI involving zero-shot and few-shot learning, knowledge injection, multimodal medical reasoning, and large pre-trained models.
My current research focuses on developing flexible and reusable pre-trained machine learning (ML) models for multimodal biomedical data involving time series, graphs, images, and text.
Concretely, my vision is to develop generalist models for biomedicine (see figure excerpt below), i.e. large, pre-trained biomedical foundation models that can flexibly ingest multiple modalities, solve dynamically specified tasks (zero-shot or few-shot) and reason over (and retrieve from) structured and editable biomedical knowledge sources.