ECE 692 - Adversarial Learning

Adversarial learning is a new research area at the intersection of machine learning, artificial intelligence, security, and digital forensics. The aim of this special topics class is to introduce graduate students to the selection of fundamental adversarial topics through focused lectures, reviews of state-of-the-art topics, and hands-on projects. The topics covered in this class will cover general adversarial perturbations, data, poisoning, bias, and misinformation.

The class will spend about 30% of the time on lectures and paper reviews, and 70% on the group research projects, where each group will focus on one research area, and will be expected to complete a research project and a research report/paper during a semester.



Course Logistics

All the reading materials, assignments and discussions will be hosted on the course Canvas web page. We have access to Google Cloud Resources through the Google Credits for Education grant.