I am a Postdoctoral researcher at the University of Paris in the LIPADE lab. I completed my Ph.D. at the University of Paris and EDF R&D, working with Prof. Themis Palpanas, Emmanuel Remy, and Mohammed Meftah. Before that, I got my bachelor’s and master’s degrees in computer science and applied mathematics from Grenoble INP ENSIMAG engineering school. Finally, 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 data series analytics and management systems.
- Unsupervised and supervised anomaly detection methods for large data series.
- Machine learning for data series classification.
- 2019-2021: PH.D. student, University of Paris, EDF R&D
- Analysis of very large multivariate time series using unsupervised learning methods in order to detect anomalies and support predictive maintenance. Collaboration with the National French Electricity company (EDF).
- 2014-2017: Master and Bachelor degree, Grenoble INP, ENSIMAG
- Engineering and Computer Science School
- 2016-2017: Exchange Program (Master), Trinity College Dublin, SCSS
- School of computer science and statistics
- (First Honor grade for First and second Semester)
- October 2022: Visiting Researcher, European Gravitational Observatory (EGO), the VIRGO collaboration
- Research project:
- Geo-localization of noises using data series from fiber-acoustic sensors positioned at one of the building of the VIRGO interferometer. Collaboration with Akis Gkaitatzis and Prof. Stavros Katsanevas.
- 2022-now: Postdoctoral researcher, Université Paris Cité, LIPADE
- Research projects:
- Benchmarking and large scale evaluation of anomaly detection methods for univariate time series. Collaboration with Dr John Paparrizos and Prof. Michael J. Franklin from the University of Chicago.
- Precursors detection and time series classification for the prediction of le Piton de la fournaise volcano. Colaboration with the Institut de Physique du Globe de Paris (IPGP).
- Ensembling unsupervised anomaly detection methods with a supervised model selection method. Evaluation on large univariate time series benchmark.
- 2017-2018: Research engineer, Ecole Polytechnique, LIX
- Research projects:
COM4U: Analysis of retail data using unsupervised learning techniques in order to discover causality links between external events and web behaviors. Collaboration with start-up Realytics. Graph mining, url clustering, time series clustering. Implementation in Python.
SMARTLAW: Analysis of law textual data using unsupervised technique in order to estimate the difficulty and the type of trial in the court of justice of France. Collaboration with the law faculty of the HEC Paris business school. Text mining, Graph modeling, Graph mining, k-core analysis. Implementation in Python.
- 2017: Research intern, Paris Descartes University, LIPADE
- Development of machine learning algorithms to detect and predict subsequence anomalies in sensor data of electric power plants. Time series similarity/clustering/classification, Matrix Profile (MP). Implementation in C and Python.
- 2016: Research intern, IRT Saint-Exupery
- Implementation of an avoidance rover protection system (ARP) in C from an Event-B model. Formal verification of the code using frama-c, why3 based ACSL language.
- 2016: Fablab project, Grenoble INP
- Design of translator gloves for sign language. Development of a functional prototype using Arduino. Machine learning (KNN-classifier) and data acquisition code (Arduino tools for online data acquisition) done in C++. More info…
Program committee member for:
Invited external reviewer for international journals:
Invited external reviewer for international conferences: