Privacy and Machine Learning

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Title: Privacy and Machine Learning

Speaker: Ran Gilad-Bachrach, Tel Aviv University

Date: September 09, Thursday
Time: 10:00 – 11:00 (Israel, UTC+03:00)
08:00 – 09:00 (UK, UTC+01:00)
03:00 – 04:00 (EDT, UTC-04:00)
17:00 – 18:00 (AEST, UTC+10:00)

Abstract:   Machine Learning (ML) technologies can create value, monetary of societal, from data. However, data collection presents privacy risks. In this talk we will discuss the different risks associated with data collected for ML purposes and present some of the technologies developed to mitigate these risks including differential privacy, Homomorphic Encryptions, Secure Multi-Party Computation, and Federated Learning.

Bio: Ran Gilad-Bachrach is a Professor at the Bio-Medical Engineering department in Tel-Aviv University where he specializes in developing machine learning tools to improve health and well-being. Ran did his studies at the Hebrew University in Jerusalem under the supervision of Prof. Naftaly Tishby. After completing his Ph.D., which focused on theoretical aspects of Machine Learning, Ran joined Intel Research to lead a research team and later joined Microsoft Research as a member of the Machine Learning Group and later the Cryptography group.