讲 座 人：Prof. Cheng Tan
联 系 人：赵传磊 firstname.lastname@example.org
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 may produce unexpected results. Our vision is to build neural networks for computer systems (NN4Sys) that satisfy pre-defined correctness properties. We call these verified NN4Sys. In this talk, I will introduce our recent attempts to pursue this vision, including building NN4Sys benchmarks, training verified NN4Sys, and applying NN4Sys in multiple systems.
Cheng Tan is an assistant professor at Khoury College of Computer Sciences at Northeastern University. His research interests are in computer systems, verifiable systems, and neural networks for systems. He is a recipient of the SOSP’17 best paper award, Janet Fabri Dissertation Prize, and NSF CAREER Award.