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I'm interested in exploring new technologies for privacy-preserving data analysis. The goal is to build software that provides rigorous privacy protection but at the same time allows researchers to analyze the data and discover aggregate trends.

AB, Dartmouth College; MS, PhD, University of Massachusetts, Amherst

Computer science, data management, data mining, and privacy and technology

Johannes Gehrke, Michael Hay, Edward Lui, and Rafael Pass
Crypto 2012

iReduct: Differential Privacy with Reduced Relative Errors
Xiaokui Xiao, Gabriel Bender, Michael Hay, Johannes Gehrke
SIGMOD 2011

Privacy-aware Data Management in Information Networks (Tutorial)
Michael Hay, Kun Liu, Gerome Miklau, Jian Pei, and Evimaria Terzi
SIGMOD 2011


Michael Hay
PhD Thesis 2010


Michael Hay, Gerome Miklau, David Jensen, Don Towsley, and Chao Li
VLDB Journal 2010

Optimizing Linear Counting Queries Under Differential Privacy
Chao Li, Michael Hay, Vibhor Rastogi, Gerome Miklau, Andrew McGregor
PODS 2010


Michael Hay, Vibhor Rastogi, Gerome Miklau, Dan Suciu
VLDB 2010


Michael Hay, Gerome Miklau, David Jensen
Draft book chapter, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques, Chapman & Hall/CRC Press. 2010


Michael Hay, Chao Li, Gerome Miklau, David Jensen
ICDM 2009

Relationship Privacy: Output Perturbation for Queries with Joins
Vibhor Rastogi, Michael Hay, Gerome Miklau, Dan Suciu
PODS 2009


Michael Hay, Gerome Miklau, David Jensen, Don Towsley, and Philipp Weis
VLDB 2008


Michael Hay, Gerome Miklau, David Jensen, Philipp Weis, and Siddharth Srivastava
University of Massachusetts Amherst Technical Report 2007


Ben Wellner, Andrew McCallum, Fuchun Peng and Michael Hay
UAI 2004

Learning relational probability trees
Jennifer Neville, David Jensen, Lisa Friedland, and Michael Hay
SIGKDD 2003


David Jensen, Jennifer Neville, and Michael Hay
ICML 2003

“Enabling Accurate Analysis of Private Network Data.”