Experiences with Learned Systems: The Good, The Bad, and The Ugly

Prof. Haibo Chen Shanghai Jiao Tong University Thursday, June 1, 2023 @ 10:00 am Room BC 420 Hosted by: Prof. James Larus

Abstract

Many problems in systems software can be transformed into those using machine learning. In this talk, I will share our past experiences of defining and optimizing optimization problems in systems software using machine learning, resulting in a set of learned systems ranging from operating systems, databases, Web systems and distributed systems. Based on these, I will further describe the learned lessons in applying machine learnings for systems, and discuss possible challenges and opportunities in fostering better synergy between systems and machine learning.

Bio

Haibo Chen is a Distinguished Professor of Shanghai Jiao Tong University, where he directs both the Institute for Parallel and Distributed Systems (IPADS). His main research areas are operating systems and distributed systems. He received Best Paper Awards from ASPLOS, EuroSys and VEE, Test of Time Award from DSN, Best Paper Honorable Mention and Research Highlight Award from SIGMOD, Honorable Mention of The Dennis M. Ritchie Thesis Award (Advisor) from SIGOPS. He currently serves on the editorial board member and co-chair of Special Sections of Communications of the ACM, Program Committee of SOSP/OSDI, and the inaugural technical steering committee chair of OpenHarmony, an open-source operating system deployed on hundreds of millions of devices. He is an IEEE Fellow and an ACM Distinguished Member.