About Me

My name is George Theodorakis and I am a Ph.D. student in the Large-Scale Distributed Systems (LSDS) group @ Imperial College London, under the supervision of Dr. Peter Pietzuch. My Ph.D. is supported by a CDT HiPEDS scholarship. Prior to this, I was an undergraduate student in the Electrical and Computer Engineering department of National Technical University of Athens and conducted my thesis under the supervision of Dr. Konstantinou in affiliation with CSLab.



Research

My research interests lie in the areas of distributed and parallel computing systems, database management systems and stream processing engines, with a current focus on optimization of streaming queries. At the moment, I am working on the design of highly efficient incremental operators with compiler-based techniques.

Publications

  1. G. Theodorakis, A. Koliousis, P. R. Pietzuch, and H. Pirk, LightSaber: Efficient Window Aggregation on Multi-core Processors in Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, SIGMOD 2020, Portland, OR, USA, Jun 2020 [GitHub]
  2. G. Theodorakis, P. R. Pietzuch, H. Pirk, SlideSide: A fast Incremental Stream Processing Algorithm for Multiple Queries in Advances in Database Technology - 23rd InternationalConference on Extending Database Technology, EDBT 2020, Copenhagen, Denmark, Mar 2020 [pdf]
  3. G. Theodorakis, A. Koliousis, P. Pietzuch and H. Pirk, Hammer Slide: Work- and CPU-efficient Streaming Window Aggregation in 9th International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures (ADMS), Rio de Janeiro, Brazil, Aug 2018. [pdf]

Projects

  1. Optimisation of streaming queries based on window semantics with code generation [GitHub]
  2. "Do We Need Distributed Stream Processing?" [blog-post] [HackerNews]
  3. Integration of Apache Calcite – a dynamic data management framework – and SABER – a hybrid relational stream processing engine. Introduction of rate-based optimisation techniques to improve the throughput, the latency and the CPU utilization of streaming queries. [GitHub] [DiplomaThesis]

Talks & Presentations

  1. SlideSide: A fast Incremental Stream Processing Algorithm for Multiple Queries in EDBT/ICDT 2020 Joint Conference, 1st April, 2020, Copenhagen, Denmark
  2. LightSaber: Efficient Window Aggregation on Multi-core Processors poster in PhD Workshop on Next-Generation Cloud Infrastructure of Microsoft Research, Cambridge, UK, Nov. 2019.
  3. "Hardware-efficient Stream Processing" in Flink Forward Berlin 2018, Berlin, Germany, Sep 2018. [slides] [video]
  4. "Hammer Slide: Work- and CPU-efficient Streaming Window Aggregation" in ADMS@VLDB 2018, Rio de Janeiro, Brazil, Aug 2018. [slides]

Education

Ph.D. student in the Large-Scale Distributed Systems Research Group
Imperial College London, United Kingdom
2017 - today
Master of Engineering in Electrical and Computer Engineering
National Technical University of Athens, Greece
2011 - 2016