Portrait of Sarah Bird

Sarah Bird

Post Doc Researcher


Sarah is postdoc at Microsoft Research NYC. Her research interests include mobile and cloud computing, machine learning, dynamic optimization, energy efficiency, parallel computer architecture, operating systems, and user experience.

Her current research focuses on problems at the intersection of systems and machine learning, particularly on designing systems that can be controlled and optimized with learning algorithms. Sarah did her Ph.D. work in computer science at UC Berkeley’s Parallel Computing Laboratory (ParLab) advised by Krste Asanovic and David Patterson at Berkeley and Burton Smith at Microsoft Research. She has B.S. in Electrical Engineering (Computer Engineering) from the University of Texas at Austin.



Established: February 17, 2016

PACORA (Performance-Aware Convex Optimization for Research Allocation) is a resource allocation framework for general-purpose operating and cloud systems, which is designed to provide responsiveness guarantees to a simultaneous mix of high-throughput parallel, interactive, and real-time applications in an efficient, scalable…

Multiworld Testing

Established: November 1, 2013

Exponentially better than A/B testing. Multiworld Testing (MWT) is the capability to test and optimize over K policies (context-based decision rules) using an amount of data and computation that scales logarithmically in K, without…