Xiaoyun Zhu

VMware University Relations

Lecture Information:
  • April 24, 2024
  • 12:04 PM
  • ECS: 241

Speaker Bio

Xiaoyun Zhu is a Staff Engineer in the VMware Cloud Resource Management Group, focusing on developing automated resource and performance management solutions for virtualized datacenters and applications. Her general interests are in applying optimization, algorithms, statistical learning and control theory to IT systems management and automation. Prior to VMware, she was a Senior Research Scientist at HP Labs for eight years.
She has co-authored over 50 refereed papers in journals and conference proceedings, and holds 19 patents. She has been a program committee member for IM, NOMS, CNSM, MASCOTS, CCGrid, Middleware, ICDCS, and SIGMETRICS.
She was the program co-chair for ICAC 2013 and will serve as the general chair for ICAC 2014, co-located with the USENIX Federated Conference Week.
Xiaoyun received her dual B.S. in Automation and Applied Mathematics from Tsinghua University in 1994, and her Ph.D. in Electrical Engineering from California Institute of Technology in 2000.


In the past decade, the IT industry has experienced a paradigm shift as computing resources became available as a utility through cloud based services. The wide adoption of server virtualization has laid a solid foundation for cloud environments, with benefits including elastic capacity, higher availability, easier deployment, higher resource efficiency, and lower energy cost. At the same time, it brings many new challenges to quality of service assurances, making it impossible for human administrators to carry out monitoring, detection, analysis, and remediation of performance problems on a 24×7 basis. These challenges present unique opportunities in applying statistical learning, control, and optimization based techniques to developing model-based, automated performance and resource management frameworks. There has been a large body of research in this area in the last several years, but many problems remain. In this talk, I’ll highlight some of the performance and resource management techniques we have developed within VMware, along with related technical challenges, and discuss open research problems, in hope to attract more innovative ideas and solutions from a larger community of researchers and developers.