The Data Science Department at EURECOM focuses on current computational, statistical and mathematical challenges in Machine Learning and Artificial Intelligence, as well as novel approaches to Knowledge and Data Management.

Our mission

The Data Science department was created in February 2016. The aim of creating this new department at EURECOM was to consolidate the research and teaching activities in Data Science, and expanding the breadth of application domains beyond the field of telecommunications, which has been the main focus of EURECOM since its creation.

Our work is defined through an interdisciplinary approach to research, merging contributions from computer science, machine learning, statistics, and mathematics. Our research program is centered around the disciplines to semantically integrate and enrich data, to model and understand data, to design and analyze scalable computational approaches to machine learning, and to build systems that allow storing and processing vast amounts of data. We address several applied problems, which motivate the development of novel theory and algorithms.

The main research lines underpinning our academic and industrial projects involve the development of a solid foundation of systems and theoretical tools to interact with and manipulate vast amounts of heterogeneous data.

Projects

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Jeunes Chercheurs Jeunes Chercheuses (JCJC) grant

Effective Inference of Cleaning Programs from Data Annotations.

KPMG Research Project

Continuous Curation of a Knowledge Base System for Data Auditing.

Google.org COVID-19 AI and data analytics

Computational methods for verifying claims and identifying misinformation about COVID-19.

Renault Software Labs

Funded Ph.D. (CIFRE) on RAW Data Fusion

Renault Software Labs

Funded Ph.D. (CIFRE) on Probabilistic Reinforcement Learning

Jeunes Chercheurs Jeunes Chercheuses (JCJC) grant

Machine learning on optical hardware.

AXA Chair

AXA Chairs are funded by the AXA Research Fund, which supports fundamental research to advance our understanding of risk.

Recent Publications

(2020). Convergence analysis of deterministic kernel-based quadrature rules in misspecified settings. Foundations of Computational Mathematics.
(2020). Creating Embeddings of Heterogeneous Relational Datasets for Data Integration Tasks. Proceedings of the 2020 International Conference on Management of Data, SIGMOD Conference 2020, online conference [Portland, OR, USA], June 14-19, 2020.

Contact

  • Campus SophiaTech, 450 Route des Chappes, Biot, 061410, France
  • Enter EURECOM campus and take the stairs/elevator to Floor -4 (right)