Theses in DIMA are often tied to ongoing research projects sponsored by funding agencies and companies. These are commonly written in English (and some in German). Problems are typically centered on topics in database systems, scalable and distributed data management, and machine learning systems, including: (i) query processing and optimization, (ii) storage, indexing, and physical database design, (iii) streams, sensor networks, and complex event processing, (iv) parallel and distributed databases, (v) databases for emerging hardware, (vi) benchmarking and performance evaluation, (vii) machine learning for data management, (viii) data management for machine learning, (ix) transaction processing, (x) database monitoring and tuning, (xi) data warehousing, OLAP, and SQL Analytics, (xii) database security, privacy, and access control, (xiii) data visualization, (xiv) graph data management, RDF, and social networks, (xv) knowledge discovery, clustering, and data mining, (xvi) spatio-temporal databases, and (xvii) very large data science applications/pipelines.
To pursue a thesis with us, students are generally required to possess:
Furthermore, to conduct a:
Moreover, depending on the thesis topic, additional knowledge may be required (e.g., compiler technology, distributed systems, networking, operating systems, systems programming, machine learning).