May 2020

The project moved from the University of Oxford to the University of Zurich along with the principal investigator and a few existing members of the team. Several current members continue to work at the University of Oxford, while other current members work at the University of Edinburgh.


September 2018

Research positions (both PhD and postdoctoral) available in our research group! Please contact Professor Dan Olteanu ( for details.


November 2018, University of Warsaw

From Joins to Aggregates and Optimization Problems

The course introduces recent development on solving a host of computational problems in the database. The unifying theme underlying this development is the use of the structure of the problem to avoid redundancy in data representation and computation.

slides part 1 part 2 part 3, video

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Research Projects (26-minute video overview)

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Principles of Factorised Databases

Principled approach to avoiding redundancy in the representation and computation of query results in relational databases. Worst-case optimal computation of compressed, factorised representations for join query results.

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In-Database Analytics

Scalable techniques for machine learning over databases that exploit the relational structure, push the learning task inside the database query engine, and factorise its computation.

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Incremental Maintenance for Analytics

Unified framework for maintaining a wide range of analytics over databases that leverages factorization for underlying queries, output data representation, and bulk updates.

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Karen Barnes

Karen is the official project administrator.

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Ahmet Kara

Ahmet earned his PhD from the University of Dortmund in the area of Logics and Automata on data words and data trees and their applications in formal system verification. He contributes to the principles of factorized computation and its incremental maintenance.

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Antonia Kormpa

Antonia earned her MSc in Computer Science and BSc in Computer Engineering and Informatics from University of Patras, Greece. She is a second year PhD student at the University of Oxford.

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Milos Nikolic

Milos earned his PhD from EPFL in database systems and in particular efficient incremental maintenance. He was a departmental lecturer in Computer Science at Oxford from Sept 2016 to Aug 2018 before joining the University of Edinburgh as a tenure-track lecturer in Databases.

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Dan Olteanu

Dan earned his PhD from the University of Munich. He was a professor of Computer Science at the University of Oxford since 2007 before joining the University of Zurich in 2020. He is the head of the FDB project.

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Fabian Peternek

Fabian earned his PhD from the University of Edinburgh in 2018 in the area of grammar-based compression of graphs. After completion he joined the FDB project as a postdoc in March 2018.

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Maximilian Schleich

Max earned his PhD in Computer Science from Oxford in 2020 on the topic of in-database analytics. He is currently a postdoctoral researcher at the University of Washington in Seattle.

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Amir Shaikhha

Amir earned his PhD from EPFL in 2018. He is a departmental lecturer in Computer Science at Oxford from Jan 2019. His contribution to the project is on compilation techniques for hybrid databases and machine learning workloads.

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Haozhe Zhang

Haozhe earned his MSc in Computer Science from Oxford. He is currently a third year PhD student and contributes to incremental maintenance of analytical workloads.

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Djordje Zivanovic

Djordje Zivanovic earned his MSc in Electrical engineering and Computer Science and BSc in Electrical engineering from University of Belgrade, Serbia. He is a second year PhD student and contributes to in-database linear algebra.