MSR Colloquium: Differential Privacy: Theoretical and Practical Challenges – Salil Vadhan, Harvard | Wednesday, August 14 @ 4 PM
WHO: Salil Vadhan
AFFILIATION: Harvard
TITLE: Differential Privacy: Theoretical and Practical Challenges
HOST: Yael Kalai
WHEN: Wed, Aug 14
WHERE: Microsoft Conference Center located at One Memorial Drive, First Floor, Cambridge, MA
SCHEDULE: 4:00 PM – 5:00 PM is the colloquium. Note: Immediately following there will be a brief reception* to meet the speaker and address detailed questions.
Abstract
Differential Privacy is framework for enabling the analysis of privacy-sensitive datasets while ensuring that individual-specific information is not revealed. The concept was developed in a body of work in theoretical computer science starting about a decade ago, largely coming from Microsoft Research. It is now flourishing as an area of theory research, with deep connections to many other topics in theoretical computer science. At the same time, its potential for addressing pressing privacy problems in a variety of domains has attracted the interest of scholars from many other areas, including statistics, databases, medical informatics, law, social science, computer security and programming languages.
In this talk, I will give a general introduction to differential privacy, and discuss some of the theoretical and practical challenges for future work in this area. I will also describe a large, multidisciplinary research project at Harvard, called "Privacy Tools for Sharing Research Data," in which we are working on some of these challenges as well as others associated with the collection, analysis, and sharing of personal data for research in social science and other fields.
Biography
Salil Vadhan is the Vicky Joseph Professor of Computer Science and Applied Mathematics at the School of Engineering & Applied Sciences at Harvard University. He is a member of the Theory of Computation research group. His research areas include computational complexity, cryptography, randomness in computation, and data privacy.