Research Topics

My research interests lie in scalable data analytics. This spans topics in database systems, distributed computing and machine learning. My current focus is designing scalable similarity search techniques for massive collections of high-dimensional vectors and exploiting them to achieve similarity-based data integration.

Publications

Below is a list of selected publications. A more complete publication record can be found here.

Tutorials

  • Karima Echihabi, Themis Palpanas. Scalable Analytics on Large Sequence Collections. International Conference on Mobile Data Management (MDM), Pafos, Cyprus, June 2022.
    (paper, slides, video)
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas. New Trends in High-D Vector Similarity Search: AI-driven, Progressive, and Distributed. International Conference on Very Large Data Bases (VLDB), Copenhagen, Denmark, August 2021.
    (paper, slides, video)
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas. High-Dimensional Similarity Search for Scalable Data Science. IEEE International Conference on Data Engineering (ICDE), Chania, Greece, April 2021.
    (paper, slides, video)
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas. Big Sequence [a.k.a. time series, or data series] Management: Scaling Up and Out. International Conference on Extending Database Technology (EDBT), Nicosia, Cyprus, March 2021.
    (paper, poster, slides, video)
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas. Big Sequence [a.k.a. time series, or data series] Management: on Scalability. IEEE International Conference on Big Data (IEEE BigData), virtual conference, December 2020.
    (paper, slides)
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas. Big Sequence [a.k.a. time series, or data series] Management. IEEE Symposium on Computers and Communications (ISCC), Rennes, France, July 2020.
    (paper, slides)
Journals
  • Ilias Azizi, Karima Echihabi, Themis Palpanas. Elpis: Graph-Based Similarity Search for Scalable Data Science. Proceedings of the VLDB Endowment (PVLDB) Journal, 2023.
    (paper, slides, video, supporting material)
  • Karima Echihabi, Theophanis Tsandilas, Anna Gogolou, Anastasia Bezerianos, Themis Palpanas. ProS: Data Series Progressive k-NN Similarity Search and Classification with Probabilistic Quality Guarantees. International Journal on Very Large Data Bases (VLDBJ), 2022.
    (paper, supporting material)
  • Karima Echihabi, Panagiota Fatourou, Kostas Zoumpatianos, Themis Palpanas, Houda Benbrahim. Hercules Against Data Series Similarity Search. Proceedings of the VLDB Endowment (PVLDB) Journal, 2022.
    (paper, slides, video, supporting material)
  • Wissam Maamar Kouadri, Mourad Ouziri, Salima Benbernou, Karima Echihabi, Themis Palpanas, Iheb Ben Amor. Quality of Sentiment Analysis Tools: The Reasons of Inconsistency. Proceedings of the VLDB Endowment (PVLDB) Journal, 2021.
    (paper)
  • Ashraf Aboulnaga, Azza Abouzeid, Karima Echihabi, Mourad Ouzzani. Database Systems Research in the Arab World: a tradition that spans decades. Communications of the ACM (CACM), 2021.
    (paper)
  • Slim Abdennadher, Sherif G. Aly, Joe Tekli, Karima Echihabi. Unleashing Early Maturity Academic Innovations. Communications of the ACM (CACM), 2021.
    (paper)
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas, Houda Benbrahim. Return of the Lernaean Hydra: Experimental Evaluation of Data Series [a.k.a. time series, or sequences] Approximate Similarity Search. Proceedings of the VLDB Endowment (PVLDB) Journal, 2019.
    (paper, supporting material)
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas, Houda Benbrahim. The Lernaean Hydra of Data Series [a.k.a. time series, or sequences] Similarity Search: An Experimental Evaluation of the State of the Art. Proceedings of the VLDB Endowment (PVLDB) Journal, 2018.
    (paper, supporting material)
Conference Articles
  • Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas. Scalable Machine Learning on High-Dimensional Vectors: From Data Series to Deep Network Embeddings. International Conference on Web Intelligence, Mining and Semantics (WIMS), Biarritz, France, June 2020.
    (paper)
  • Anna Gogolou, Theophanis Tsandilas, Karima Echihabi, Anastasia Bezerianos, Themis Palpanas. Data Series [a.k.a. time series, or sequences] Progressive Similarity Search with Probabilistic Quality Guarantees. ACM SIG International conference on Management of Data / Principles of Database Systems (SIGMOD/PODS), Portland, OR, USA, June 2020.
    (paper, suppporting material)
  • Karima Echihabi (supervised by Themis Palpanas and Houda Benbrahim). Truly Scalable Data Series [a.k.a. time series, or sequences] Similarity Search. Very Large Data Bases (VLDB) PhD Workshop, Los Angeles, CA, USA, August 2019.
    (paper)