CISE Seminar: Cheng Tan, Assistant Professor, Northeastern University

March 4, 2022
3:00pm-4:00pm
Hybrid Event: PHO 210 & Zoom

Constructing Certified Neural Networks

Deep learning and neural networks are powerful tools. Applying them in computer systems—operating systems, databases, and networked systems—attracts much attention. However, neural networks are complicated black boxes that sometimes produce unexpected results. It is risky to use networks with uncertain behaviors in computer systems that require strict safety rules.

To tame the network’s uncertainty, we introduce Ouroboros, a system that constructs certified neural networks. Certified neural networks are neural networks that satisfy user-defined safety properties, named specifications. Ouroboros achieves this through a training-verification loop that combines deep learning training and neural network verification. In addition, Ouroboros supports three categories of specifications and has a specification language that allows ordinary developers to write specifications easily. With Ouroboros, people, for example, system developers, can have faith in their neural networks.

Cheng Tan is an assistant professor of Khoury College of Computer Sciences at Northeastern University. His research interests are in systems and security, focusing on building verifiable outsourced services and certified neural networks for systems. His work has won SOSP’17 best paper award and Janet Fabri Prize for Outstanding Dissertation.

Faculty Host: Alan Liu
Student Host: Saeed Mohammadzadeh