Alessandro Panconesi is full professor of Computer Science at Sapienza, University of Rome. He holds a PhD degree in Computer Science from Cornell University. He was the recipient of the ACM Danny Lewin Award. Last year he was awarded a Google Focused Award and, previously, he received research faculty awards from IBM, Yahoo and Google. His main current research interest are distributed and randomised algorithms for social networks.

AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, MMCI   Info

Expert Audience

English

60 Minutes

Kaiserslautern

Abstract: In recent years, we have witnessed the emergence of many sophisticated web services that allow people to interact on an unprecedented scale. The wealth of data produced by these new ways of communication can be used, in principle, to increase our understanding of human social behaviour, but a fundamental hurdle is posed by the sensitivity of these data. Access must of necessity be severely constrained in order to protect the privacy of the users and the confidentiality of the data. A very broad question arises naturally: can non-trivial conclusions about various social processes be inferred based only on such limited information? We give a few specific examples taken from our own research of what can, and cannot, be learned from digital traces.
The talk describes joint work with several people: B.Abrahao, P.Brach, F.Chierichetti, R.Kleinberg, A.Epasto, P.Sankowski

Brigitta Hansen

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