Big Data Engineering

Team

The DAMS Lab (data management for data science laboratory) is a cross-organizational research group uniting the chair for big data engineering at TU Berlin and external members from multiple universities and industry.

Master theses (completed):   Svetlana Sagadeeva (2020), Simon Kysela (2021), Florijan Klezin (2022), Florian Lackner (2022), Pooja Veeresh Yeli (2022), Mito Kehayov (2022), Michael Hofer (2023), Vlad-Andrei Dumitru (2023), Christina Dionysio (2023), Philipp Ortner (2023), Damian Dinoiu (2024)

Bachelor theses (completed):  Benjamin Rath (2019), Sandro Letter (2020), Valentin Edelsbrunner (2021), Tobias Rieger (2021), Kevin Innerebner (2021), Thomas Krametter (2022), Thomas Wedenig (2022), Jonathan Resch (2022), Olga Ovcharenko (2022), David Weissteiner (2022), Dževad Ćoralić (2022), Lukas Erlbacher (2022), Jonathan Haberl (2023), Gabriel Alexandru Muresan (2023), Emil Winterleitner (2023), Mario Schwaiger (2023), Richard Bendler (2023), Mark Paranskij (2023), Fares Kataf (2023), Danial Alnicola (2023), Elias Strauß (2023)

We're looking for motivated PhD, master, and bachelor students to join our team. Our research focuses on building ML systems and tools for simplifying the data science liefecycle – from data integration over model training to deployment and scoring – via high-level language abstractions and specialized compiler and runtime techniques. If you're interested, please contact us directly via email to jobs@dams.tu-berlin.de.