I’m a Research Engineer at Google DeepMind. My research is focused on advancing the state-of-the-art in systems using machine learning, often referred to as ML for Systems. In my current work I focus on improving the efficiency and performance of huge-scale systems by exploiting features and patterns that can be found using machine learning. My projects span many different components of systems including consensus, bug finding, caching, indexing, and query optimization.

Prior to joining Google I received my PhD in Computer Science from Cornell University. During my PhD I focused on building Distributed Systems that rely on strong foundations in Distributed Systems Theory. I specialized in consensus protocols, replication, and evolving systems. Since my PhD I have also been maintaining, which focuses on helping developers understand and implement the Paxos consensus algorithm.

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