Soheil Feizi

Assistant Professor, CS @ UMD

I am a faculty in Computer Science department at University of Maryland, College Park (UMD). I am also affiliated with University of Maryland Institute for Advanced Computer Studies (UMIACS). My research spans various theoritical and practical aspects of Machine Learning.
Before joining UMD, I was a a post-doctoral research scholar at Stanford University . I received my Ph.D. and M.Sc. in Electrical Engineering and Computer Science, with a minor degree in Mathematics, at MIT.


My research focuses on understanding various theoretical and practical aspects of machine learning and statistical inference problems. In particular, I am keen to understand the robustness of modern learning methods with respect to the learning architecture and model complexity, noise (either random or adversarial) and the amount of training data.

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I am teaching CMSC 726 (the graduate level Machine Learning Course) in Fall 2018. In this course, we will start with classical learning models and work towards modern problems such as GANs and adversarial learning. This course will be a mix of theory and applications. 

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Note to Prospective Students:

I am looking for students and post-docs with CS, Stats/Math or EE backgrounds, who are interested in working in theoritical and practical aspects of machine learning and statistical learning problems.

Information for prospective students can be found here.

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Talk @ Google Research


I am giving a talk titled "GANs: model-based or model-free?" in google research.

First Day @ UMD


I am officially starting my faculty career at CS@UMD.

Machine Learning Course


I am teaching CMSC 726 in Fall 2018.