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Research profile

Odysseas Papapetrou is Assistant Professor in the Information Systems group in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e). He is an experienced Big Data researcher, with expertise in real-time processing of streaming data and a specialty in approximation algorithms for distributed Big Data management, distributed data streams processing and sketching/summarization techniques. Papapetrou also focuses on aspects of cloud computing such as cloud federations, cloud-based stream processing and privacy-preserving query execution. 

Papapetrou frequently serves as a PC member and reviewer for data management conferences and journals, such as TKDE and VLDB Journal. He is also a regular grants evaluator for the Hong Kong Research Grants Council (RCG), and an occasional evaluator for other funding schemes. 

Academic background

Odysseas Papapetrou got his BSc in Computer Science and an MSc in Advanced Information Technologies from the University of Cyprus. He then went on to do an MSc in Computer Science at the University of Saarland and Max Planck Institute (2005) and a PhD in Computer Science at the University of Hannover and L3S Research Center (2011). Then he started working as a researcher at SoftNet Lab, Technical University of Crete (2011-2015), and as an adjunct lecturer at the Open University of Cyprus (2012-2013)In 2016, Papapetrou moved to EPFL, Switzerland, where he worked as a Research and Teaching Associate, and later as an EPFL Marie Skłodowska-Curie FellowIn 2018, Papapetrou joined Eindhoven University of Technology (TU/e) as Assistant Professor. 

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 11 - Sustainable Cities and Communities

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  • Easy spark

    van den Wildenberg, Y., Nuijten, W. & Papapetrou, O., 2021, Proceedings of the Workshops of the EDBT/ICDT 2021 Joint Conference, Nicosia, Cyprus, March 23, 2021. Costa, C. & Pitoura, E. (eds.). CEUR-WS.org, 6 p. (CEUR Workshop Proceedings; vol. 2841).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Open Access
  • A parallel and distributed approach for diversified top-k best region search

    Shahrivari, H., Olma, M., Papapetrou, O., Skoutas, D. & Ailamaki, A., 1 Jan 2020, Advances in Database Technology - EDBT 2020: 23rd International Conference on Extending Database Technology, Proceedings. Bonifati, A., Zhou, Y., Vaz Salles, M. A., Bohm, A., Olteanu, D., Fletcher, G., Khan, A. & Yang, B. (eds.). OpenProceedings.org, p. 265-276 12 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Open Access
    1 Citation (Scopus)
  • Data stream statistics over sliding windows: how to summarize 150 million updates per second on a single node

    Chrysos, G., Papapetrou, O., Pnevmatikatos, D., Dollas, A. & Garofalakis, M., Sep 2019, Proceedings - 29th International Conference on Field-Programmable Logic and Applications, FPL 2019. Sourdis, I., Bouganis, C-S., Alvarez, C., Toledo Diaz, L. A., Valero, P. & Martorell, X. (eds.). Piscataway: Institute of Electrical and Electronics Engineers, p. 278-285 8 p. 8892241

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    4 Citations (Scopus)
    1 Downloads (Pure)
  • Scalable temporal clique enumeration

    Zhu, K., Fletcher, G., Yakovets, N., Papapetrou, O. & Wu, Y., 19 Aug 2019, Proceedings of the 16th International Symposium on Spatial and Temporal Databases, SSTD 2019. New York: Association for Computing Machinery, Inc, p. 120-129 10 p. (ACM International Conference Proceeding Series).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    1 Citation (Scopus)
    2 Downloads (Pure)
  • Taster: self-tuning, elastic and online approximate query processing

    Olma, M., Papapetrou, O., Appuswamy, R. & Ailamaki, A., 1 Apr 2019, Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019. Piscataway: IEEE Computer Society, p. 482-493 12 p. 8731505

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    4 Citations (Scopus)
    3 Downloads (Pure)