I am an Assistant Professor in the School of Computer Science at McGill University, where I lead the Data-Intensive Storage and Computer Systems Laboratory (DISCS Lab). My current focus is on storage and persistent memory technologies, with an emphasis on the way we manage large-scale data for machine learning, data science and edge computing workloads. I also hold a status-only appointment at the University of Toronto.

I completed my PhD in Computer Science at the University of Sydney in 2020, advised by Prof. Willy Zwaenepoel. My dissertation research was on the design and implementation of efficient key-value stores for future  hardware and performance requirements. My PhD was generously supported by The University of Sydney Faculty of Engineering and IT Dean's Postgraduate Research Scholarship and by the EPFL Fellowship for Doctoral Studies. I have earned my Bachelors and Masters degrees in Computer Science from EPFL

Contact: oana.balmau@mcgill.ca

Office: McConnell 113N

Currently, I do not have any open positions for PhD students.

Please read this before sending me email.

Current research: DISCS Lab

I am lucky to work with many amazing students and collaborators. Meet the team and have a look at my group's ongoing research here.

Data powers everything we do and we are collecting it at unprecedented rates. The driver for research at DISCS is to create a storage infrastructure that enables us to gain insights from this data in a fast and energy-conscious manner.

Our two main research directions are:

See more details on the DISCS page.

Previous Research: Key-value Stores

Key-value stores (KVs) are a crucial component in cloud computing because they can efficiently handle large-scale, diverse data (e.g., deployed in the infrastructure of Google, Apple, Facebook, and Amazon). In my dissertation, Redesigning Persistent Key-Value Stores for Future Workloads, Hardware, and Performance Requirements, I proposed new techniques to improve persistent KVs. I designed and built four novel open-source systems: TRIAD, FloDB, SILK, and KVell.  For an overview, have a look at my job talk.


Awards and Honors


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About Me

Outside of research, I enjoy: