Bio

Marc Juarez is a Lecturer in Cyber Security and Privacy at the University of Edinburgh’s School of Informatics, where he is a member of the Security, Privacy, and Trust group (SecPrivTru).

Research

Marc’s research addresses the security and privacy risks introduced by machine learning systems, along three main lines: resistance to traffic analysis, the security and trustworthiness of AI deployments, and the privacy and fairness properties of machine learning models.

A 2024 Google Research Scholar Award in Security and a GAIL seed grant fund his work on provenance techniques for generative AI, including watermarking and fingerprinting schemes for image-generation models. A separate award from Amazon Research supports his research into the trustworthiness of AI and machine learning tools used in automated hiring.

Teaching

At Edinburgh, Marc developed and teaches Privacy and Security with Machine Learning (PSML), and has taught Computer Security (CSEC) since 2023. He also supervises several PhD and MSc students each year. See the teaching page for details.

Academic Background

Marc obtained his PhD from KU Leuven, under an FWO PhD fellowship. There, in the Computer Security and Industrial Cryptography (COSIC) group, he applied machine learning techniques to a wide range of security and privacy problems; his dissertation, in particular, studies the application of machine learning to web traffic fingerprinting attacks. By developing novel website fingerprinting methods and identifying pitfalls in how such methods are typically evaluated, his work has advanced our understanding of the threat they pose to web users, and has informed the design of defenses now used in several privacy-enhancing technologies and deployed systems. One of the publications from his dissertation won the 2016 ESORICS Best Paper Award, and the dissertation itself was a runner-up for the 2020 ACM SIGSAC Doctoral Dissertation Award.

Before joining the University of Edinburgh, Marc was a Postdoctoral Scholar in the Computer Science Department of the University of Southern California (USC), where he worked on problems related to privacy and algorithmic bias.

Education

Appointments