Kay Ousterhout

Kay Ousterhout serves as an Assistant Teaching Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, where she teaches CS 61A: The Structure and Interpretation of Computer Programs. She previously worked as a TA for CS61B and developed educational materials for data science courses including a lab on Apache Spark.

Her research focuses on performance analysis and optimization in distributed data processing systems, with particular emphasis on Apache Spark. She has made significant contributions as a committer and PMC member for Apache Spark, developing high-throughput schedulers (Sparrow and Drizzle) and creating Monotasks - a system designed to make performance reasoning accessible to users. Her work bridges the gap between theoretical system design and practical performance challenges in real-world data analytics.

Ousterhout completed her PhD in Computer Science at UC Berkeley in 2017 under Sylvia Ratnasamy in the NetSys Lab, following her B.S.E. in Computer Science from Princeton University in 2011 where she worked with Jennifer Rexford and Michael J. Freedman. Her research has been published in top-tier systems conferences including SOSP, NSDI, and HotOS.

Her notable achievements have been recognized through prestigious awards:

• Google PhD Fellowship
• Hertz Foundation Graduate Fellowship
• UC Berkeley Chancellor's Fellowship
• Google Anita Borg Memorial Scholarship

In addition to her academic role, Ousterhout works as a software engineer at LightStep, focusing on performance understanding in complex distributed systems. She actively contributes to open source projects and regularly presents her research at major conferences, demonstrating her commitment to advancing both academic knowledge and practical industry solutions in distributed systems.