I'm a postdoc researcher in the DAMS Lab research group headed by Matthias Boehm at Technische Universität Berlin and the BIFOLD research center in Berlin, Germany. My research interests are centered around database systems, machine learning systems, and techniques for making complex analyses of large data volumes efficient, scalable, and simple. In that context, my current topics of interest include extensible data systems, compilation and runtime techniques, as well as language abstractions for declarative analyses. The main vehicle of this research is DAPHNE, an open and extensible system infrastructure for integrated data analysis pipelines combining data management and query processing, machine learning training and scoring, as well as high-performance computing and simulations.

Until fall 2022, I was a university project assistant at Graz University of Technology and a senior researcher (postdoc) at the co-located Know-Center GmbH in Graz, Austria. During that time, I started my research in the DAPHNE EU-project and became one of the main contributors of the DAPHNE system.

Before that, in 2020, I received my PhD (Dr.-Ing.) from Technische Universität Dresden in Dresden, Germany, where I was a research associate in the Dresden Database Systems group. I was supervised by Wolfgang Lehner and co-supervised by Dirk Habich. In my PhD thesis, I investigated the use of lightweight integer compression for the intermediate results of complex OLAP queries in in-memory column stores as a means to address the memory wall. This work led to the development of MorphStore, a research prototype of a query processing engine for columnar data, based on compression and SIMD as first-class citizens. I've also collaborated with colleagues on topics like SIMD, NVRAM, resilience, and energy efficiency in database systems.