Recent Publications

International Conference & Workshop:

  • H. El Hafyani, M. Abboud, J. Zuo, K. Zeitouni and Y. Taher: “Tell Me What Air You Sense/Breath, I Tell You Where You Are”, (demo) International Symposium on Spatial and Temporal Databases 2021 (SSTD’21)
  • M. Abboud, H. El Hafyani, J. Zuo, K. Zeitouni and Y. Taher: “Micro-environment Recognition in the context of Environmental Crowdsensing”, in Big Mobility Data Analytics with EDBT 2021 (BMDA’21)
  • J. Zuo, K. Zeitouni and Y. Taher: “Incremental and Adaptive Feature Exploration over Time Series Stream”. (regular paper) IEEE International Conference on Big Data (IEEE BigData 2019), Los Angeles, CA, USA, 2019
  • J. Zuo, K. Zeitouni and Y. Taher: “ISETS: Incremental Shapelet Extraction from Time Series Stream“,(demo paper) European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD’19), Würzburg, Germany, 2019
  • J. Zuo, K. Zeitouni and Y. Taher. “Exploring Interpretable Features for Large Time Series with SE4TeC”, (demo paper) 22nd International Conference on Extending Database Technology (EDBT’19), Lisbon, Portugal, 2019. [Poster]

National Conference:

Community Service

Organizing committees:

  • MDM 2020 Web Chair of the 21st IEEE Mobile Data Management Conference
  • JDSE 2019 Junior organization committee of the 4th Paris-Saclay Junior Conference on Data Science and Engineering

Program committees:

  • ECML-PKDD 2020 The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases

Reviewing:

  • ICDE 2021 IEEE International Conference on Data Engineering
  • AAAI 2021 AAAI Conference on Artificial Intelligence
  • SSTD 2021 International Symposium on Spatial and Temporal Databases
  • DSAA 2020 IEEE International Conference on Data Science and Advanced Analytics

Projects

PROJECT STREAMOPS - INSTITUT DATAIA

  • Open Source Platform for Research and Integration of Algorithms for Massive Time Series Flow Analysis
  • The goal of StreamOps is to develop methods and algorithms to consider temporal order in data streams.

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