Ran Gilad-Bachrach, Ph.D.

Professor of Biomedical Engineering

Tel Aviv University

Speech Title:

Private AI

Abstract:

One of the main obstacles to applying AI in the health domain is gaining access to data due to its sensitivity and due to strict regulations. In this talk we will present methods that have been developed in recent years to address the data access challenge by combining Machine-Learning techniques with Cryptography. We will show the different challenges that emerge in the different stages of the value chain and the techniques available for addressing these challenges.

Bio:

Professor Ran Gilad-Bachrach is leading the MLwell lab, in the Bio-Medical engineering Department at Tel-Aviv University. The lab studies machine learning and its applications for health and wellbeing. Ran earned his Ph.D. from the Hebrew University of Jerusalem. After graduating, Ran founded a machine-learning research group in Intel research and later joined Microsoft, first as an applied researcher in the Bing search engine and later as a principal researcher in Microsoft Research. In 2019 Ran Joined Tel-Aviv university as an Associate Professor. Ran published over 40 papers in the leading venues of machine learning and AI. Among his contributions are machine-learning algorithms that preserve privacy, algorithms for parallel training, algorithms for learning on graphs and sets, methods for using AI to help people cope with mental stress, and many additional contributions. Ran is the head of the Digital Sciences for Hi-Tech program at Tel-Aviv university, a member of the steering committee of Clinical Bioinformatics Program at the Safra Center, a member of Sagol Brain Research Center, and a technical member of the Belle II experiment, a high-energy accelerator research organization.