George Siachamis

I am a PhD Candidate at the Web Information Systems group of the Faculty of Engineering, Mathematics and Computer Science at Delft University of Technology. I am also part of AI for Fintech Research, a collaboration between TU Delft and ING. I am supervised by Asterios Katsifodimos. My research is focused on adaptive stream processing, and specifically adaptive similarity joins over data streams, autoscaling and live state migration, while I have also worked on data discovery.

Before pursuing a PhD, I did my research internship at CY Cergy Paris University under the supervision of Katerina Tzompanaki. Prior to that, I obtained my 5-year Diploma in Electrical and Computer Engineering from National Technical University of Athens.

PhD Candidate, Web Information Systems Group, Department of Software Technology,
Faculty of Electrical Engineering, Mathematics and Computer Science, TU Delft
Integrated Master of Engineering (M.Eng), Faculty of Electrical and Computer Engineering,
National Technical University of Athens (NTUA)

Adaptive Distirbuted Streaming Similarity Joins

George Siachamis, Kyriakos Psarakis, Marios Fragkoulis, Odysseas Papapetrou, Arie van Deursen, Asterios Katsifodimos
In the Proceedings of the 17th International Conference in Distributed and Event-based Systems (DEBS) 2023.
Towards Evaluating Stream Processing Autoscalers

George Siachamis, Job Kanis, Wybe Koper, Kyriakos Psarakis, Marios Fragkoulis, Arie van Deursen, Asterios Katsifodimos
In the Self-Managing Database System (SMDB) Workshop of the 2023 IEEE International Conference on Data Engineering (ICDE).
Valentine: Evaluating matching techniques for dataset discovery

Christos Koutras, George Siachamis, Andra Ionescu, Kyriakos Psarakis, Jerry Brons,
Marios Fragkoulis, Christoph Lofi, Angela Bonifati, Asterios Katsifodimos
In the Proceedings of the 2021 IEEE International Conference on Data Engineering (ICDE).
Valentine in action: matching tabular data at scale

Christos Koutras & Kyriakos Psarakis , George Siachamis, Andra Ionescu,
Marios Fragkoulis, Angela Bonifati, Asterios Katsifodimos.
In the Proceedings of the 47th International Conference on Very Large Data Bases (VLDB) 2021 (Demo track).
Integrating Massive Data Streams

George Siachamis
In Proceedings of the VLDB 2021 PhD Workshop, August 16th, 2021.

News

DEBS 2023

Our paper "Adaptive Distributed Streaming Similarity Joins" is accepted at the 17th International Conference in Distributed and Event-based Systems (DEBS 2023). Join the presentation on the 1st session on 28th of June in Neuchatel.

SMDB 2023

We presented our paper "Towards Evaluating Stream Processing Autoscalers" in the Self-Managing Database Systems workshop, co-located with ICDE 2023 in Anaheim, California.

Valentine as a python library

We have created a python library with the algorithms included in Valentine. Have access to the state-of-the-art algorithms for Schema Matching and Dataset Discovery, by simply running 'pip install valentine'.