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Theoretical research includes the development of novel data processing algorithms and languages along with the analysis of their complexities.
Systems research is on building data systems in academia and industry based on well-understood theory.
Principled approach to avoiding redundancy in the representation and computation of query results in relational databases
Machine Learning over Relational Data
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
Unified framework for maintaining a wide range of analytics over databases that leverages factorization for underlying queries, output data representation, and bulk updates
Adaptive Dynamic Query Processing
Trade-offs in static and dynamic evaluation of conjunctive queries
Optimal Joins over Interval Data
Charting the tractability of Boolean conjunctive queries with intersection joins via equivalence to disjunctions of Boolean conjunctive queries with equality joins
Efficient and numerically accurate QR. SVD and PCA decompositions of matrices defined by joins over relational data
Research positions (both PhD and postdoctoral) available in our research group! If you are intrigued by the kind of research we do, please consider applying. [ More Information ]
