I am generally interested in the intersection of data management and machine learning. This includes questions such as how to make machine learning scalable, decentralized, and private – ideally at the same time – or how to build data infrastructures that benefit the common good.

My PhD research focuses on designing and implementing cross-silo federated learning systems. The goal of my work is to enable different organizations or individuals to jointly execute federated computations across multiple data silos. More concretely, I work on systems that support the end-to-end process from the initial discovery of interested parties to a final evaluation of the result. For that, I use techniques from data management, data discovery, data integration, algorithmic privacy, and machine learning. Beyond my core PhD research, I have also been exploring other topics in the field of data management in collaboration with colleagues or as part of advising theses.

I am always looking for great students and collaborators. If you are interested in writing a BSc/MSc thesis with me or working as a Research Assistant at DIMA, send me an email explaining your interest and attach an up-to-date CV.


ICDE '23
PDF Code

The Art of Losing to Win: Using Lossy Image Compression to Improve Data Loading in Deep Learning Pipelines

Lennart Behme, Saravanan Thirumuruganathan, Alireza Rezaei Mahdiraji, Jorge-Arnulfo Quiané-Ruiz, and Volker Markl.

39th IEEE International Conference on Data Engineering (2023).

CDMS '22

Towards a Modular Data Management System Framework

Haralampos Gavriilidis, Lennart Behme, Sokratis Papadopoulos, Stefano Bortoli, Jorge-Arnulfo Quiané-Ruiz, and Volker Markl.

1st International Workshop on Composable Data Management Systems @ VLDB (2022).

You can also find me on dblp or Google Scholar.


  • Software Campus Grant for the project “Federated-Data-as-a-Service”
  • Honored by the Electrical Engineering and Computer Science Faculty at TU Berlin for one of the three best 2021/22 Information Systems Management degrees
  • Five-time recipient of the Deutschlandstipendium scholarship (awarded to 1.5% of the student body)


  • Summer ‘23
    • Information Systems and Data Analysis ISDA
  • Winter ‘22
    • Database Lab DBPRA
  • Summer ‘22
    • Information Systems and Data Analysis ISDA
    • Seminar on Advanced Topics in Database and Information Systems DBSEM
    • Database Project DBPRO
  • Winter ‘21
    • Research Oriented Course on Data Science and Engineering Systems and Technologies ROC
    • Seminar on Hot Topics in Information Management IMSEM


  • Investigating the Effectiveness of Cross-Silo Datasets for Training Federated Learning Models
    Florian Haberkorn B.Sc.
  • Query Relaxation for Numerical Query Predicates
    Seungmi Lee B.Sc.

Community Service

  • External reviewer SIGMOD 2023
  • Member of the Availability Committee SIGMOD 2023
  • External reviewer ICDE 2023
  • External reviewer CIDR 2023