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The research of the database systems group focuses on data-intensive systems. A key focus are issues related to dynamic and time-varying information, including query processing, query optimization, scalable algorithms, and query languages. Ongoing research activities also include processing and analyzing time series data, in-database machine learning, similarity search, scientific and spatial data processing, and graph data processing.
The research of the database systems group is based on the construction of data-centric solutions that leverage AI technologies. We design and implement large-scale systems, develop algorithms and data structures with precise algorithmic complexity analyses, and do system-based experiments. The emphasis is on mathematically precise results that solve actual real-world problems. We develop algorithms and systems to validate, communicate, and disseminate our research results.
Our work is published in the flagship outlets of the database systems community (SIGMOD, VLDB, TODS, VLDBJ and ICDE) and we integrate our solutions into the kernels of popular and emerging database engines, such as PostgreSQL, MonetDB, Timescale, DuckDB and Kuzu.