Assistant Professor, Delft University of Technology (TU Delft).
Member of the Web Information Systems group.

Before joining TU Delft, I spent a year with the SAP Innovation Center in Berlin, working on scale-out architectures for machine learning inference and training. Before SAP, I was a senior researcher at the database systems group in TU Berlin, headed by Volker Markl. I received my PhD from INRIA Saclay & Universite Paris-Sud in 2013, under the supervision of Ioana Manolescu. Prior to that, I was a member of the High Performance Computing systems Lab (HPCL), at the University of Cyprus, working with Marios Dikaiakos.

I work in the broad area of scalable data management; more specifically on data management and analysis, stream processing, systems for scalable AI/ML, and data integration. I work with Marios Fragkoulis (postdoc) and Christos Koutras (PhD student, co-advised with Christoph Lofi).

I am the information director of SIGMOD Record, a local organization chair of SIGMOD 2019 and I regularly serve in the program committees of ICDE/SIGMOD and VLDB.

Asterios Kαtsifodimos - Αστέριος Κατσιφοδήμος


Office VBM6 4.E.080 (4th floor)
Van Mourik Broekmanweg 6
2628XE Delft
  • June 2019: We are presenting a demo in this year’s VLDB on how to execute stateful functions in the cloud, using streaming dataflows (pdf), as well as a paper on how to optimize ML pipelines using both linear and relational algebra.
  • March 2019: We received the best paper award from EDBT 2019 for our paper “Efficient Window Aggregation with General Stream Slicing”!
  • January 2019: One full-paper and one vision paper at EDBT 2019.
  • December 2018: A poster paper was accepted at ICDE 2019.
  • March 2018: I serve as a local organization chair of SIGMOD 2019 which will be held in Amsterdam in 2019!
  • January 2018: Two papers were accepted in next year’s ICDE 2018 in Paris. One on benchmarking stream procesing engines, and one on aggregating out-of-order streams.
  • August 2017: BlockJoin, a technique for joining massive datasets producing distributed block-partitioned matrices, will be presented in next year’s VLDB 2018.
  • June 2017: At SoCC 2017 we are presenting our work on SENSE, a framework for sensor-data gathering.
  • August 2016: We will present Cutty, a technique for sharing aggregates among user-defined (sliding) window functions in streaming systems, at CIKM 2016.
  • March 2016: We published a short overview of Apache Flink in the IEEE Data Engineering Bulletin (pdf).
  • February 2016: Our paper on Emma, was accepted for publication at SIGMOD 2015, and will be demonstrated in SIGMOD 2016. Emma received the 2016 ACM SIGMOD Research Highlights Award! More information here.

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