Core Data Science (CDS)

Advancing the frontiers of data science

About Core Data Science (CDS)

Core Data Science (CDS) is a research and development team, working to improve Facebook’s products, infrastructure, and processes. We generate real-world impact through a combination of scientific rigor and methodological innovation. Our focus is on longer-term, foundational work that addresses new opportunities and challenges across the Facebook family of apps. The work we do enhances products that enable more than 1.5 billion people to communicate with each other, every day.

Core Data Science is interdisciplinary, with expertise in computer science, statistics, machine learning, economics, political science, operations research, and sociology, among many other fields. This diversity of perspectives enriches our research and expands the scope and scale of projects we can address. We deliver value through collaborative projects with other groups at Facebook and with the academic community. In addition, we build and open-source technical products aligned with our areas of expertise.

Engaging with the academic community is of key importance to our research group. We publish findings, host PhD students through our internship program, collaborate with professors and PhD students, and highlight open areas of interest through our request for research proposals.

Core Data Science researchers work from the Facebook offices in Menlo Park, New York, Washington D.C., London, and Tel Aviv.

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Latest Publications

All Publications

Multiplicative Pacing Equilibria in Auction Markets

Vincent Conitzer, Christian Kroer, Eric Sodomka, Nicolas E. Stier-Moses

Operations Research Journal - July 1, 2021

Stochastic bandits for multi-platform budget optimization in online advertising

Vashist Avadhanula, Riccardo Colini Baldeschi, Stefano Leonardi, Karthik Abinav Sankararaman, Okke Schrijvers

The Web Conference - April 21, 2021

Multi-armed Bandits with Cost Subsidy

Deeksha Sinha, Karthik Abinav Sankararaman, Abbas Kazerouni, Vashist Avadhanula

AISTATS - April 13, 2021

The Decoupled Extended Kalman Filter for Dynamic Exponential-Family Factorization Models

Carlos A. Gómez-Uribe, Brian Karrer

JMLR - February 11, 2021