I am a Postdoctoral Research Fellow at the Department of Biomedical Data Science. My research focuses on developing machine learning and statistical models to solve problems that are inter-disciplinary in nature, including those from the biomedical, ecological, and socio-political sciences. I received my Ph.D. in Computer Science from University of Zurich, Switzerland in 2019, where I developed new algorithms to improve recommendation diversity and algorithmic fairness. I used graph theory, deep learning, and latent-factor models to build documents representations, explainable knowledge base embeddings, and personalization systems. At Stanford, I am building new machine learning models for personalized medicine by combining biological domain knowledge and large heterogeneous datasets. My research spans both ends of the biomedical data spectrum: from single-cell observations to population health data. I am particularly interested in examining the disparate health impacts of environmental factors on vulnerable and minority populations and in understanding how these findings can guide policy interventions.