Reihaneh Torkzadehmahani

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 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

Interests:

• Machine Unlearning
• Label Noise Learning
• Responsible Machine Learning
• Generative Models

Education:

• M.Sc. in Computer Science, 2019
  University of California, Santa Cruz, United States
• M.Sc. in Artificial Intelligence and Robotics, 2015
  Iran University of Science and Technology, Iran
• B.Sc. Computer Engineering, 2013
  University of Kerman, Iran