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boniolp/README.md

Hi there, I'm Paul Boniol 👋

I am a researcher at Inria, member of the VALDA project-team, which is a joint team between Inria Paris, École Normale Supérieure, and CNRS.

Before that, I was a Postdoctoral researcher at Ecole Normale Supérieure (ENS) Paris Saclay (Centre Borelli) in the team of Prof. Laurent Oudre. I completed my Ph.D. at the University of Paris and EDF R&D, working with Prof. Themis Palpanas, Emmanuel Remy, and Mohammed Meftah. During my Ph.D., I did an internship at the University of Chicago under the supervision of Prof. Michael J. Franklin and Prof. John Paparrizos. Before starting my Ph.D., I worked as a research engineer at the computer science lab of Ecole Polytechnique in Prof. Michalis Vazirgiannis's team.

My research interest lies in the intersections between:

  • Massive time series analytics and management systems.
  • Unsupervised and supervised anomaly detection methods for large time series.
  • Machine learning for time series analytics.

You may find more info on my personal website

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  1. Theseus Theseus Public

    [VLDB 2022] Dash application for "Navigating the Labyrinth of Time Series Anomaly Detection"

    Python 21 2

  2. dCAM dCAM Public

    [SIGMOD 2022] Python code for "Dimension-wise Class Activation Map for Multivariate Time Series Classification"

    Jupyter Notebook 16 1

  3. MSAD MSAD Public

    [VLDB 2023] Model Selection for Anomaly Detection in Time Series

    Jupyter Notebook 26 3

  4. TheDatumOrg/TSB-UAD TheDatumOrg/TSB-UAD Public

    An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection

    Jupyter Notebook 162 52

  5. TheDatumOrg/VUS TheDatumOrg/VUS Public

    Jupyter Notebook 64 42

  6. adrienpetralia/ApplianceDetectionBenchmark adrienpetralia/ApplianceDetectionBenchmark Public

    [ACM e-Energy23] Appliance Detection Using Very Low Frequency Smart Meters Time Series

    Python 16 1