Benjamin RubinsteinBenjamin Rubinstein
Senior Lecturer (equiv US Assistant Professor)
Dept. Computing & Information Systems
The University of Melbourne, Australia 

Affiliations:
Fellow, Centre for Business Analytics, Melbourne Business School [link]
Associate Investigator, ARC Centre of Excellence for Mathematical & Statistical Frontiers [link]


[firstname].[lastname]@unimelb.edu.au
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Office 7.21 Doug McDonell Building

Juliet & Ella   Liam   Lachlan

 
Interests: Statistical Machine Learning, Security & Privacy, Databases, Industry Engagement

Bio: Ben joined the University of Melbourne in 2013 as a R@MAP appointee, as a Senior Lecturer in Computing and Information Systems. Previously he gained four years of US industry experience in the research divisions of Microsoft, Google, Intel and Yahoo!; 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); and his research has helped identify and plug side-channel attacks against the popular Firefox browser. He actively researches topics in machine learning, security, privacy, and databases. 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.

Service

Funding

Other News

  • 12/2016: University leadership panel, Cyber in Business Conference, ANZ Centre Docklands, Melbourne
  • 12/2016: Invited speaker at the Emerging Big Data Technologies Summit, Melbourne
  • 05/2016: Invited speaker at the National Fintech Cyber Security Summit at the Ivy, Sydney hosted by Data61, Stone & Chalk, the Chief Scientist of Australia.
  • 04/2016: Speaking at Telstra (data science)
  • 02/2016: Speaking at Samsung Research America and UC Berkeley.
  • 02/2016: Speaking in two exciting panels at AAAI'2016 on keeping AI beneficial and challenges for AI in cyber operations.
  • 12/2015: Plenary at the 12th Engineering Mathematics and Applications Conference (EMAC'2015) the biennial meeting of the EMG special interest group of ANZIAM
  • 07/2015: Keynote at the Australian Academy of Science Elizabeth and Frederick White Research Conference on Mining Data for Detection and Prediction of Failure in Geomaterials [link]
  • 12/2014: Excellence in Research Award 2014, Dept CIS, University of Melbourne
  • 11/2014: Facebook (Menlo Park) talk Data Integration through the Lens of Statistical Learning

Research Group

  • Postdocs
    • Yi Han (2016 - ). Adversarial machine learning.
  • PhD students
    • Lingjuan Lyu (w Marimuthu Palaniswami 2016 - ). Privacy in distributed sensing.
    • Neil Marchant (w Aurore Delaigle 2016 - ). Adaptive sampling.
    • Yuan Li (w Trevor Cohn 2015 - ). Bayesian optimisation, NLP.
    • Xunyun Liu (w Raj Buyya, Rodrigo Calheiros 2015 - ). Stream computing.
    • Safiollah Heidari (w Raj Buyya 2015 - ). ML for distributed computing.
    • Yamuna Kankanige (w James Bailey 2015 - ). Liver transplant outcomes, Austin Health
    • Zay Aye - CompSci (w Rao Kotagiri 2014 - ). Learning distance metrics.
    • Maryam Fanaeepour - CompSci (w Lars Kulik, Egemen Tanin 2014 - ). Location data privacy.
    • Jiazhen He - CompSci (w James Bailey, Rui Zhang 2014 - ). Education analytics and MOOCs.
    • Zuhe Zhang - Maths & Stats (w Sanming Zhou 2014 - ). Differential privacy in Bayesian statistics.
  • Masters students
    • Current: Si Chen
    • Completed: Rui Hu, Justin Liang, Nouras Fatima, Zhe Lim (2014); Ben Schroeter, Soundarya Mallemarapu (2015); Samuel Jenkins, Xianjing Fan (2016)
  • Interns from Microsoft Research

Teaching

Publications

2016

2015

2014

2012

2011 

2010

2009

2008

2007

Pre 2007