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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 paxos.systems, which focuses on helping developers understand and implement the Paxos consensus algorithm.
To contact me you can use one of the icons on the right.
News
News
On the PC for SOSP'25.
Serving as a reviewer on ML for Systems @NeurIPS'24.
Serving as reviewer on MLArchSys 2024 @ ISCA.
I will be co-chairing ATC'25. September, 2023.
Serving as a reviewer on ATC'24. October, 2024.
Our paper Snowcat: Efficient Kernel Concurrency Testing using a Learned Coverage Predictor has been accepted to SOSP’23.
Serving as a reviewer on NeurIPS'23: ML for Systems. July, 2023.
Guest Lecture at UIUC on ML for Systems. September, 2022.
Serving as a reviewer on VLDB Journal. September, 2022.
Co-chairing PACMI Workshop at MLSys. September, 2022.
Co-chairing ACM SoCC'22. April, 2022
Talk at Koç University on ML for Systems. May, 2022
Serving as a PC Member for NSDI’23. April, 2022
Giving a talk at the UC Berkeley Sky Seminar titled "The Tip of the Iceberg: How to make ML for Systems work" March, 2022
Serving as a PC Member for FAST’23. March, 2022
Serving as a PC Member for ACM Web Conference 2022. November, 2021
Giving a guest lecture at MIT about Learned Indexes for a Google-scale Disk-based Database. October, 2021
Serving as an industrial PC Member for EDBT’22. October, 2021
Serving as a PC Member for OSDI’22. October, 2021
Serving as a PC Member for ML for Systems at NeurIPS. August, 2021
Co-organizing the Work-in-Progress and Poster sessions at FAST’22. August, 2021
Our paper Snowboard: Finding Kernel Concurrency Bugs through Systematic Inter-thread Communication Analysis has been accepted to SOSP’21. August, 2021
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