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Programming and verification frameworks for differential privacy
Host: Prof. Patrick Eugster
USI Campus EST, sector D, room D0.02
13:15 - 14:15
UPDATE - SEMINAR NEW DATE
Differential Privacy is a formal notion of data privacy that has found application in the public and private sectors. It offers ways to answer statistical queries about sensitive data while providing strong provable privacy guarantees ensuring that the presence or absence of a single individual in the data has a negligible statistical effect on the query’s result.
In this talk I will first introduce the basics of differential privacy, some of the fundamental mechanisms for building differentially private programs, and some applications that use differential privacy. I will then overview a few language-based approaches developed to help programmers to guarantee their differentially private programs.
Marco Gaboardi is an Associate Professor in Computer Science at Boston University. Before joining Boston University, he has been on the faculty at the University at Buffalo, SUNY, and at the University of Dundee, UK. Marco received his PhD from the University of Torino, Italy, and the Institute National Polytechnique de Lorraine, France. He has been a visiting scholar at the University of Pennsylvania, at Harvard University’s CRCS center, and at the Simons Institute for the Theory of Computing, UC Berkeley. He is a recipient of an EU Marie Curie Fellowship, an NSF Career Award, a Caspar Bowden Award for Outstanding Research in Privacy Enhancing Technologies and a Google Research Award. Marco's research is in programming languages, formal verification, and in differential privacy.
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