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Room 3 - Foundations

Thursday June 13th, 12:30-13:15

Compiling to preserve our privacy

About this Session

Move over data analytics, secure machine learning is here. As privacy becomes an increasingly important concern, so does the need to analyze data securely. Secure multi-party computation (MPC) is a promising solution that helps different entities collaborate in training ML models, while also keeping their data private.

For applications to truly scale, we need to implement models in a high-level language, abstracting away the low-level MPC details: we need a compiler! In this talk we describe the unique aspects of writing a compiler so that developers and data scientists need not be crypto experts.

Required Knowledge

Basic Scala and compiler knowledge, and some basic cryptography notions.

Speaker(s)

Manohar Jonnalagedda
@manojah_shanti

Manohar is a Senior Software Engineer at Inpher, a company developing solutions for secure computing. He has a PhD in Programming Languages (advised by Martin Odersky) and worked on Program Synthesis tools as a post-doc at MSR India.

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