Meta Research

I am a Software Engineer at Meta's Data Infrastructure org (DI). I'm interested in building novel systems with a focus on large-scale data platforms (query processing and optimization), systems for machine learning, and cluster resource management.

At Meta, I am involved in various parts of DI's data analytics stack. Currently, I am leading an effort for enabling dataframe-like APIs on top of Meta's analytics engines, and I'm also involved in efforts related to query optimization and the distributed execution runtime.

Prior to joining Meta in 2022, I was a Principal Research Scientist at Microsoft. I was a member of Microsoft's Gray Systems Lab, Azure Data's applied research group, first as an individual contributor and then as a manager. The last 3 years at Microsoft, I led an effort for the execution and optimization of ML prediction queries in Azure's data engines. Before that, my work focused mainly on resource management for Microsoft's production analytics clusters and was key to enable the company to operate the world’s largest YARN clusters. Prior to Microsoft, I was with IBM Research at Almaden.

I have published in database and systems conferences (including SIGMOD, VLDB, OSDI) and regularly serve in their committees. I also contributed a big part of my work to open-source projects: I am a committer and PMC member of Apache Hadoop, and a contributor to ONNX Runtime and Presto. I hold a PhD from Inria and the University Paris-Sud, France, and a Diploma in Electrical and Computer Engineering from the National Technical University of Athens, Greece.