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