Rate My Professor Sarah Monazam Erfani

Sarah Monazam Erfani is a Professor in the School of Computing and Information Systems at the University of Melbourne, part of the Faculty of Engineering and Information Technology. She received her PhD from the University of Melbourne in 2015, focusing on anomaly detection in participatory sensing networks. Following her PhD, she served as a Research Fellow in Computing and Information Systems from 2015 to 2016. Her career has advanced through positions such as Senior Lecturer to her current role as Associate Professor and ARC DECRA Fellow. Erfani's research interests encompass machine learning, AI safety and reliability, cybersecurity, data privacy, and IoT analytics. She has developed scalable methods for unsupervised learning with practical applications in telecommunication network management. As an Associate Investigator for the University of Melbourne node of the ARC Centre of Excellence for Automated Decision-Making + Society (ADM+S), she contributes to advancements in these areas. She is affiliated with the AI Assurance Lab and supervises PhD students in artificial intelligence.

Erfani has earned major awards including the ARC Discovery Early Career Researcher Award (DECRA) in 2022 for $403,482, the Women in AI Award for Defence and Intelligence in 2024, and the Young Tall Poppy Science Award for Victoria in 2025. Her work has accumulated over 7,800 citations according to Google Scholar. Key publications include "Unlearnable Examples: Making Personal Data Unexploitable" (2021) co-authored with Hanxun Huang, Xingjun Ma, James Bailey, and Yisen Wang, addressing privacy protection against machine learning exploitation; "Backdoor Attacks on Time Series: A Generative Approach" (2023); and "An Anomaly Detection Framework for Decision-Making Sequences." She has authored articles in Pursuit by the University of Melbourne, such as on using quantum computing to protect AI from attacks and blocking AI access to personal data. Her research influences AI reliability and security in academic and practical settings.