Machine Learning for Cybersecurity
Instructors

Yuxin Chen
Assistant Professor, Department of Computer Science
Yuxin Chen is an assistant professor at the Department of Computer Science at the University of Chicago. Previously, he was a postdoctoral scholar in Computing and Mathematical Sciences at Caltech, hosted by Prof. Yisong Yue. He received his Ph.D. degree in Computer Science from ETH Zurich, under the supervision of Prof. Andreas Krause. He is a recipient of the PIMCO Postdoctoral Fellowship in Computing and Mathematical Sciences, a Swiss National Science Foundation Early Postdoc.Mobility fellowship, and a Google European Doctoral Fellowship in Interactive Machine Learning.
His research interest lies broadly in probabilistic reasoning and machine learning. Yuxin is currently working on developing interactive machine learning systems that involve active learning, sequential decision making, interpretable models and machine teaching. You can find more information in his Google scholar profile.

Nick Feamster
Neubauer Professor of Computer Science; Faculty Director, Center for Data and Computing
Nick Feamster is the Neubauer Professor in the Department of Computer Science and the College, and faculty director of the Center for Data and Computing.
His research applies large-scale Internet measurement and machine learning to address problems in Internet performance, security and privacy, censorship, and the Internet of Things. His work aims to make networks easier to manage, more secure, more available, and an overall better experience for consumers.
Nick is an ACM Fellow and is also a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE) for his contributions to cybersecurity, notably spam filtering. Prior to joining UChicago, Prof. Feamster was a full professor at Princeton University, where he directed the Center for Information Technology Policy (CITP).

Blase Ur
Neubauer Family Assistant Professor of Computer Science and the College
Blase Ur researches computer security, privacy and human-computer interaction. His focus is on helping users make better security and privacy decisions, and improving user experience within complex computer systems. Asst. Prof. Ur founded the UChicago SUPERgroup, an interdisciplinary research collective comprised of dozens of researchers who work on computer security, privacy and usability. He has also worked extensively on supporting users’ online privacy, as well as studying both privacy and interaction aspects of the Internet of Things.
He has received best paper awards from CHI, the 2016 USENIX Security Symposium, and the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing. In addition, he has strong interests in teaching and K–12 outreach, particularly with the goal of broadening participation in computer science.