Ben actively research topics in machine learning, security & privacy, databases such as adversarial learning, differential privacy and record linkage. Prior to joining the University of Melbourne in 2013, he enjoyed four years in the research divisions of Microsoft, Google, Intel and Yahoo! (all in the United States), 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; 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. Since joining Melbourne in 2013, Ben have led $2.0m in awarded competitive funding ($1.2m per CI). His work has been recognised through an Australian Research Council DECRA award, and a Young Tall Poppy Science award.
Zhang, D., Rubinstein 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