ZENITH Team: Gestion de données scientifiques

Reza AKBARINIA

Head

ZENITH Team

Scientific Data Management

The three main challenges of scientific data management can be summarized as follows: (1) scale (large data, large applications); (2) complexity (uncertain data, multi-scale, with many dimensions), (3) heterogeneity (in particular, the semantic heterogeneity of data). They are also those of data science, whose goal is to make sense of data by combining data management, machine learning, statistics and other disciplines.

Zenith’s overall goal is to address these challenges by offering innovative solutions with significant benefits in terms of scalability, functionality, ease of use and performance. To produce generic results, these solutions are in terms of architectures, models and algorithms that can be implemented in terms of components or services in clusters or the cloud.

We design and validate our solutions by working closely with our scientific application partners such as INRAe and CIRAD in France, or MACC in Brazil. To further validate our solutions and extend the reach of our results, we also encourage industrial collaborations, even in non-scientific applications, provided they present similar challenges.

Members

Staff
Esther Pacitti, Professeur des universités, UM
Florent Masseglia, Directeur de recherche, INRIA
Alexis Joly, Directeur de recherche, INRIA
Reza Akbarinia, Chargé de recherche, INRIA
Cathy Desseaux, Assistant ingénieur, INRIA
Benjamin Bourel, Chargé de recherche, INRIA
Christophe Botella, Chargé de recherche, INRIA
Jean-Christophe Lombardo, Ingénieur de recherche, INRIA
Antoine Affouard, Ingénieur d’étude, INRIA

Associates and Students
Matteo Contini, IFREMER
Kawtar Zaher, INA (Institut National de l’Audiovisuel)
Raphael Benerradi, UM
Guillaume Coulaud, UM
Théo Larcher, UM
Cesar Leblanc, INRIA
Loai Gandeel, INRIA

Regular Co-workers
Benoit Lange, CDD Ingénieur-Technicien, INRIA
Thomas Paillot, CDD Ingénieur-Technicien, INRIA
Jean Baptiste Fermanian, CDD Chercheur, UM
Julien Thomazo, CDD Ingénieur-Technicien, CNRS
Mathias Chouet, Invité longue durée Mission longue, CIRAD
Nadine Jacquet, CDD Ingénieur-Technicien, CNRS
Maxime Ryckewaert, CDD Chercheur, INRIA
Fabio Machado Porto, CDD Chercheur, INRIA
Axel Vaillant, CDD Ingénieur-Technicien, INRIA
Rebecca Pontes Salles, CDD Chercheur, INRIA
Pierre Leroy, CDD Ingénieur-Technicien, INRIA
Hugo Gresse, CDD Ingénieur-Technicien, INRIA
Lukas Picek, CDD Chercheur, INRIA
Patrick Valduriez, Invité longue durée Eméritat, INRIA
Joseph Salmon, Invité longue durée Délégation, INRIA
Maxime Fromholtz, CDD Ingénieur-Technicien, INRIA
Raphael De Freitas Saldanha, CDD Chercheur, INRIA

Research Topics

Our approach is to capitalise on the principles of distributed and parallel data management. In particular, we exploit: high-level languages as a basis for data independence and automatic optimisation; data semantics to improve information retrieval and automate data integration; declarative languages (algebra, calculus) to manipulate data and workflows; and highly distributed and parallel environments such as P2P, cluster and cloud. To reflect our approach, we organise our research programme into five complementary themes:

Data integration, including polystores;
Query processing, including indexing and privacy; and
Management of scientific workflows;
Data analysis, including data mining and statistics;
Machine learning for high-dimensional data processing and retrieval.

PhDs's defended

Title: Une approche prédictive de la détermination du statut de conservation conjoint des espèces
PhD defendant: Joaquim Estopinan
Defense date: 2023-11-28
Thesis directors: François Munoz, Alexis Joly

Title: Interprétabilité des modèles de distribution despèces basés sur des réseaux de neurones convolutifs
PhD defendant: Benjamin Deneu
Defense date: 2022-11-24
Thesis directors: François Munoz, Alexis Joly

Title: Techniques de segmentation adaptative pour une représentation efficace des séries temporelles
PhD defendant: Lamia Djebour
Defense date: 2022-09-13
Thesis directors: Reza Akbarinia, Florent Masseglia

Title: Gestion distribuée de workflows scientifiques pour le phénotypage des plantes à haut débit
PhD defendant: Gaetan Heidsieck
Defense date: 2020-12-09
Thesis director: Esther Pacitti

Title: Incertitude des prédictions dans les modèles d’apprentissage profonds appliqués à la classification fine
PhD defendant: Titouan Lorieul
Defense date: 2020-12-02
Thesis director: Alexis Joly

Title: Clustering Massivement Distribué via Mélange de Processus de Dirichlet
PhD defendant: Khadidja Meguelati
Defense date: 2020-03-13
Thesis director: Florent Masseglia

Title: préservation de la confidentialité des données externalisées dans le traitement des requêtes top-k
PhD defendant: Sakina Mahboubi
Defense date: 2018-11-21
Thesis director: Patrick Valduriez

Title: Indexation et analyse de très grandes masses de séries temporelles
PhD defendant: Djamel Yagoubi
Defense date: 2018-03-19
Thesis director: Florent Masseglia

Title: Traitement de requêtes dans les systèmes multistores
PhD defendant: Paule Carlyna Celnare Bondiombouy
Defense date: 2017-07-12
Thesis director: Patrick Valduriez

Title: Representations basées sur les voisins partagés pour la classification fine
PhD defendant: Valentin Leveau
Defense date: 2016-11-09
Thesis directors: Patrick Valduriez, Alexis Joly

Title: Gestion multisite de workflows scientifiques dans le cloud
PhD defendant: Ji Liu
Defense date: 2016-11-03
Thesis directors: Esther Pacitti, Patrick Valduriez

Title: Parallel Itemset Mining in Massively Distributed Environments
PhD defendant: Saber Salah
Defense date: 2016-04-20
Thesis directors: Florent Masseglia, Reza Akbarinia