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 responsively improve people’s lives. Her primary focus is on enhancing the responsibility of machine learning models by enabling them to unlearn specific training data upon user request and improving their robustness to label noise. Prior to joining TUM, she earned her second M.Sc. degree in Computer Science from the University of California, Santa Cruz, where her thesis focused on generating differentially private synthetic images using generative adversarial networks.