Prof. Feizi is a faculty member in the Computer Science department at the University of Maryland, College Park (UMD). He is also affiliated with University of Maryland Institute for Advanced Computer Studies (UMIACS) and ECE. His research spans various theoritical and practical aspects of Machine Learning.
Before joining UMD, he was a a post-doctoral research scholar at Stanford University. He received his Ph.D. and M.Sc. in Electrical Engineering and Computer Science, with a minor degree in Mathematics, at MIT.
His research focuses on understanding various theoretical and practical aspects of machine learning and statistical inference problems. In his group, they are working on problems related to Generative Adversarial Networks (GANs), Variational AutoEncoders (VAEs), Adversarial examples, the optimization landscape of deep learning, its interpretability and generalization, etc.
- Machine Learning
- Data Science