Training Machines to Help Doctors and Scientists Prevent Unhealthy Pregnancies

Welcome to the intersection of maternal-fetal medicine and artificial intelligence (AI). I am dedicated to improving pregnancy care by leveraging machine learning. Through medical AI, our work aims to provide solutions that improve pregnancy outcomes.

My research is centered on understanding the causes and prevention of preeclampsia, extending to similar conditions encompassed by the great obstetrical syndrome. I focus on prognostic predictive modeling and causal inference, particularly applying structural causal modeling. I am interested in a diverse range of data, either observational or experimental, such as electronic health records, high-throughput data, and wet lab experiment data to develop a comprehensive understanding of these complex conditions.

Discover more and feel free to contact me here.