Multimedia Indexing & Data Integration
MIDI
The MIDI group works in the field of Big Data Management and Analytics, addressing topics that include integrating, mining, analyzing and querying large volumes of various types of data, ranging from structured and semi-structured data, to spatiotemporal data, text, image, video and 3D models.
A particular emphasis is put on the design and use of Machine Learning techniques in contexts specific to data analysis and data processing problems, with a focus on the explainability and transparency of such algorithms.
Applications include social media content and graph analytics, semantic web data integration and analysis, pattern detection in image, video and multimodal data, search engines for different types of data, knowledge extraction from data, data privacy, etc.
The application domains are vast, such as cultural heritage, security, opinion mining, health, etc.
Team
PhD Student
PhD Student
PhD student attached to the team MIDI
MCF, ENSEA
EUTOPIA PhD co-tutelle fellow
Professor emeritus
Doctorant
PU, CY Cergy Paris University
PU, CY Cergy Paris University
PU, CY Cergy Paris University
EC, CY TECH, CY Cergy Paris University
MCF, ENSEA
PU, ENSEA, MIDI Group Leader
Ingénieur de recherche
EC, CY Tech, CY Cergy Paris University
MCF, CY Tech, CY Cergy Paris University
MCF, CY Cergy Paris University
Research areas
Responsible Data Science
Transparency, fairness of data-intensive programs. Explainable data quality management. Data Privacy.
Data Integration and Analytics for multiple modalities
Massive Data Integration for linked and streaming data. Analysis and mining of social networks (graph structure and text). Mobility and spatio-temporal data analytics. Indexing, analysis and search of data from multiple modalities.
Distributed, Online and Deep Learning
Deep Learning for computer vision. Anomaly detection for sequence, streaming data. Graph based learning.
