Abstract: The recent development of AI technologies has been the most prominent driving force for the latest research across all research areas. In an effort to explore emerging research problems and opportunities at the exciting intersection between computer systems and machine learning, we organized the SysML workshop that brings together researchers from both academia and industry to speak about the problem they are interested in and the emerging research trends that may change the landscape of ML + System research. In particular, this workshop aimed to explore the design of computer systems from the ground up to enable principled ML-driven optimization, and explore new theoretical ML questions that must be addressed to ensure that systems offer the desired performance, robustness, and safety in practice. In this presentation, I'll present the highlights of this workshop and the lessons we have learned from the presentation and discussion. 

Speaker Bio: Le Xu is a postdoc researcher of computer science at the University of UT Austin, working with Prof. Aditya Akella at UT Networked Systems group (UTNS). She is a recipient of CIFellow 2021, supported by both the National Science Foundation (NSF) and the Computing Research Association (CRA). Her current research mainly revolves around all aspects of resource-efficient cloud computing frameworks, including serverless computing and alternative system architectures.