Reihaneh Torkzadehmahani is a Ph.D. student at the chair for AI in Medicine at the Technical University of Munich (TUM). Her ultimate research goal is to bridge the gap between theory and practice in building machine learning systems that robustly and provably improve people’s lives. She is mainly interested in the social aspects of machine learning such as privacy and fairness, especially for medical applications. Before joining TUM, she obtained her (2nd) M.Sc. degree in Computer Science at the University of California, Santa Cruz, and her thesis focused on generating differentially private synthetic images using generative adversarial networks.