Dr. Steffen Zeuch
Dr. Steffen Zeuch
Research Group Lead
RESEARCH GROUP LEAD: “DISTRIBUTED DATA STREAM PROCESSING IN HETEROGENEOUS ENVIRONMENTS”
Researcher | German Research Center for Artificial Intellligence (DFKI)
- Cloud Computing
- Big Data
- HPC
- In-memory databases
- Distributed Computing
Xenofon Chatziliadis, Eleni Tzirita Zacharatou, Alphan Eracar, Steffen Zeuch, Volker Markl
Efficient Placement of Decomposable Aggregation Functions for Stream Processing over Large Geo-Distributed Topologies
David Justen, Daniel Ritter, Campbell Fraser, Andrew Lamb, Nga Tran, Allison Lee, Thomas Bodner, Mhd Yamen Haddad, Steffen Zeuch, Volker Markl, Matthias Böhm
POLAR: Adaptive and Non-invasive Join Order Selection via Plans of Least Resistance
Dwi P. A. Nugroho, Philipp M. Grulich, Steffen Zeuch, Clemens Lutz, Stefano Bortoli, Volker Markl
Benchmarking Stream Join Algorithms on GPUs: A Framework and Its Application to the State of the Art
Ariane Ziehn, Philipp M. Grulich, Steffen Zeuch, Volker Markl
Bridging the Gap: Complex Event Processing on Stream Processing Engines
Philipp M. Grulich, Steffen Zeuch and Volker Markl
Towards Efficient and Secure UDF Execution with BabelfishLib (Lightning Talk)
“POLAR” lowers the adoption barrier for adaptive query processing in database systems
A preprint by BIFOLD researchers titled "POLAR: Adaptive and Non-invasive Join Order Selection via Plans of Least Resistance" is set to be presented at the VLDB conference in 2024. The database engineering paper introduces a technique for reordering joins that is adaptive, with a focus on non-invasive integration and low overhead.
EDBT conference 2024
The EDBT conference 2024 took place from March 25 to 28. BIFOLD researchers presented three papers at this Core-A conference on databases: "Benchmarking Stream Join Algorithms on GPUs: A Framework and its Application to the State of the Art", "Bridging the Gap: Complex Event Processing on Stream Processing Engines", and “Evaluation of Sampling Methods for Discovering Facts from Knowledge Graph Embeddings”.
VLDB honors NebulaStream demo
A perfect conclusion for the BIFOLD team at VLDB 2023 in Vancouver: The Nebula Stream team received an honorable mention for the best demo. In total, eleven researchers from the team of BIFOLD director Volker Markl participated in VLDB 2023 in Vancouver, one of the most important database conferences worldwide.
TU Berlin and DFKI database systems researchers offer multiple presentations at VLDB 2020
Researchers at TU Berlin Database Systems and Information Management (DIMA) group and Intelligent Analytics for Massive Data (IAM) group at DFKI presented one full paper, one demo paper and three PhD thesis papers at the 46th International Conference on Very Large Databases (VLDB 2020).
An overview of the current state of research in BIFOLD
Since the official announcement of the Berlin Institute for the Foundations of Learning and Data in January 2020, BIFOLD researchers achieved a wide array of advancements in the domains of Machine Learning and Big Data Management as well as in a variety of application areas by developing new Systems and creating impactfull publications. The following summary provides an overview of recent research activities and successes.
Newest work on the Nebulastream system by database systems researchers of TU Berlin and DFKI will be presented at VLIoT 2020
The Paper “NebulaStream: Complex Analytics Beyond the Cloud” by Steffen Zeuch et al. was accepted for presentation at the 2020 International Workshop on Very Large Internet of Things (VLIoT 2020). VLIoT 2020 will take place in conjunction with the VLDB 2020 conference.
In this paper, the NebulaStream (NES) project team in DFKI’s IAM group and TU Berlin’s DIMA group shows why there is a need for a new End-to-End data processing systems for the Internet of Things (IoT).
Database systems research paper accepted for publication in VLDB Vol. 13
The Paper “Dynamic Parameter Allocation in Parameter Servers” authored by Alexander Renz-Wieland, Rainer Gemulla, Steffen Zeuch and Volker Markl from was accepted for publication in Proceedings of the VLDB Endowment Vol. 13.
Paper on adaptive sampling and filtering for IoT accepted at DEBS 2020
The paper “A Survey of Adaptive Sampling and Filtering Algorithms for the Internet of Things”, authored by D. Giouroukis et al. has been accepted for presentation at the 14th ACM International Conference on Distributed and Event-Based Systems (DEBS 2020), 13. – 17. July 2020 in Montreal, Canada.
BIFOLD researchers receive SIGMOD 2020 best paper award
Database systems researchers at TU Berlin, HPI and DFKI were highly successful this year. Four of their papers were accepted at the 2020 ACM SIGMOD/PODS International Conference on the Management of Data. And, in particular, one of the paper’s received the 2020 ACM SIGMOD Best Paper Award. The paper entitled “Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects,” by Clemens Lutz, Sebastian Breß, Steffen Zeuch, Tilmann Rabl (now at HPI), and Volker Markl explores the use of GPUs to accelerate database query processing.
Three papers presented at EDBT 2020
Researchers in TU Berlin’s Database Systems and Information Management (DIMA) Group and DFKI’s Intelligent Analytics for Massive Data (IAM) Group presented three systems papers at EDBT 2020, the 23rd International Conference on Extending Database Technology, held from March 30 to April 2. Originally planned to take place in Copenhagen, Denmark, this year’s EDBT conference was held online instead.
Four papers authored by TU Berlin and DFKI researchers have been accepted at SIGMOD 2020
Data management systems researchers in the Database Systems and Information Management (DIMA) Group at TU Berlin and the Intelligent Analytics for Massive Data (IAM) Group at DFKI (the German Research Institute for Artificial Intelligence) were informed that their papers have been accepted at the 2020 ACM SIGMOD/PODS International Conference on the Management of Data.