Ben joined the University of Melbourne in 2013 as a Senior Lecturer in Computing and Information Systems (a RAMAP appointee). Previously he gained four years of industry experience in the research divisions of Microsoft, Google, Intel and Yahoo! (all in the US); followed by a short stint at IBM Research Australia. As a full-time Researcher at Microsoft Research, Silicon Valley, Ben shipped production systems for entity resolution in Bing and the Xbox360 (driving huge success accounting for revenues in the $100m's); his research has helped identify and plug side-channel attacks against the popular Firefox browser, and deanonymise an unprecedented Australian Medicare data release, prompting introduction of the Re-identification Offence Bill 2016. He actively researches topics in machine learning, security & privacy, databases such as adversarial learning, differential privacy and record linkage respectively. His work has been recognised through an Australian Research Council DECRA award, and a Young Tall Poppy Science award. Ben earned the PhD in Computer Science from UC Berkeley under Peter Bartlett in 2010, collaborating closely with the SecML group, at the boundary of machine learning and security.
Zhang, D., Rubenstein B.I.P., & Gemmell J.
(2015). Principled Graph Matching Algorithms for Integrating Multiple Data Sources. IEEE Transactions on Knowledge and Data Engineering. 27(10), 2784-2796. doi: 10.1109/TKDE.2015.2426714