Our systems work is interdisciplinary, drawing across colleagues with expertise in programming languages, networking, distributed systems, cryptography, privacy and security. We break silos and innovate across various layers in the systems stack spanning hardware, networks, storage, and compute.

Our research projects include:

  • Co-designing storage and compute layers for big data systems, as well as scheduling, compilation and run-time layers for DNN jobs to improve end-to-end efficiency.
  • Building query optimizers that are able to handle modern query languages that incorporate not only SQL-like relational operators, but also user-defined logic expressed in full-featured programming languages.
  • Developing formal verification and design methods to build correct software, and applying these ideas to improve the robustness and security for large scale concurrent and distributed real-world systems.
  • Working at the intersection of cryptography and systems, to design new ways for secure data exchange and collaboration, and new block-chain systems at unprecedented scale and performance.
  • Tracking data lineage and provenance at scale to help ensure data privacy.

We harness the power of machine learning to use data driven techniques to better optimize not only the systems themselves, reduce costs and improve performance, but to also make significant improvements to engineering processes used to build such systems.


Sankie devops illustration


Project Sankie infuses data-driven techniques into engineering processes, development environments, and software lifecycles of large services.


Micro Co-design 

The massive scale of cloud infrastructure services enables, and often necessitates, vertical co-design of the infrastructure stack by cloud providers. Micro co-design is a Minimally invasive, Cheap, and retro-fittable approach to co-design that extracts efficiency out of existing software infrastructure layers. It does…

HAMS: Harnessing AutoMobiles for Safety 

In the Harnessing AutoMobiles for Safety (HAMS) project, we use low-cost sensing devices to construct a virtual harness for vehicles. The goal is to monitor the state of the driver and how the vehicle is being driven in the context…

EzPC system figure

EzPC (Easy Secure Multi-party Computation) 

Consider the following scenario: two hospitals, each having sensitive patient data, must compute statistical information about their joint data. Privacy regulations forbid them from sharing data in the clear with any entity. So, can they compute this information while keeping…