Speaker: Gil Cohen, Princeton University
Title: Recent advances in randomness extractors and their applications
A randomness extractor is a function that "extracts" or "purifies" the randomness of a defective source of randomness. Randomness extractors have applications in abundance and unexpected connections to error-correcting codes, expander graphs and pseudorandom generators. In this talk we present recent developments in randomness extractors theory and applications to classical, long-standing, open problems such as Ramsey graphs constructions and privacy amplification protocols.
Gil Cohen is a postdoctoral researcher at Princeton University. He obtained his Ph.D. in 2015 from The Weizmann Institute of Science under the guidance of Ran Raz. In 2015-16 he was a postdoctoral fellow at Caltech, hosted by Leonard Schulman and Thomas Vidick. His interests lie mostly in theoretical computer science with a focus on computational complexity, pseudo-randomness, and explicit constructions.
Talk sponsored by: Depts.of Computer Science/Mathematics
For additional information contact Steve Easterbrook