[Colloquium] CANDIDATE INTERVIEW TODAY: Ashwin Machanavajjhala, Yahoo! Research

Katie Casey caseyk at cs.uchicago.edu
Fri Mar 16 08:23:10 CDT 2012


DEPARTMENT OF COMPUTER SCIENCE

UNIVERSITY OF CHICAGO

Date: Friday, March 16, 2012
Time: 2:30 p.m.
Place: RY 251

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Speaker:		Ashwin Machanavajjhala

From:		Yahoo! Research

Web page:	http://research.yahoo.com/Ashwin_Machanavajjhala

Title: 		No Free Lunch in Data Privacy	

Abstract:		Tremendous amounts of personal data about individuals is being collected and shared online. Legal requirements and an increase in public awareness due to egregious breaches of individual privacy have made data privacy an important field of research. Recent research, culminating in the development of a powerful notion called differential privacy, have transformed this field from a black art into a rigorous mathematical discipline. 
This talk critically analyzes trade-off between accuracy and privacy in the context of social advertising – recommending people, products or services to users based on their social neighborhood. I will present a theoretical upper bound on the accuracy of performing recommendations that are solely based on a user's social network, for a given level of (differential) privacy of sensitive links in the social graph. I will show using real networks that good private social recommendations are feasible only for a small subset of the users in the social network or for a lenient setting of privacy parameters.

I will also describe some exciting new research about a no free lunch theorem, which argues that privacy tools (including differential privacy) cannot simultaneously guarantee utility as well as privacy for all types of data, and conclude with directions for future research in data privacy and big-data management. 

Bio : Ashwin Machanavajjhala is a Senior Research Scientist in the Knowledge Management group at Yahoo! Research. His primary research interests lie in data privacy with a specific focus on formally reasoning about privacy under probabilistic adversary models. He is also interested inbig-data management and statistical methods for information integration. Ashwin graduated with a Ph.D. from the Department of Computer Science, Cornell University. His thesis work on defining and enforcing privacy was awarded the 2008 ACM SIGMOD Jim Gray Dissertation Award Honorable Mention. He has also received an M.S. from Cornell University and a B.Tech in Computer Science and Engineering from the Indian Institute of Technology, Madras.

Host: Ian Foster

Refreshments will be served in Ryerson 255 following the talk at 3:30.
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