Industrial Area

Big Data & Data Science

Innovative data analytics solutions

The Big Data & Data Science Department at Eurecat designs, builds and validates innovative data analytics solutions to optimise business processes and improve decision-making by creating and adapting new technologies and algorithms.

Experience

aprendizaje profudno

Data mining and machine learning

  • Recommendation systems
  • Data mining
  • User behaviour mining
  • Graphics mining
nueva economia

New Data Economy

  • Big data analytics platforms
  • Personal data management systems
algoritmo

Privacy & Algorithmic Fairness

  • Online conversation analysis
  • Information dissemination and influence on social media
  • Fake news detection
  • Participation and digital democracy platforms
  •  Human mobility and geoanalysis
sensores

Perception & Cognition

  • Behavioural and psychophysiological measures
  •                 Multi-modal portable sensors for field studies with users
datos masivos

Big Data Infraestructures

  • Stream processing
  • In-house cloud infrastructure
  • Spatio temporal data management
  • NOSQL data management
xarxes socials

Social Media & computational Social Science

  • Detection of targeted advertising and price discrimination online
  • Auditing of algorithms and discrimination
  • Anonymisation platforms

Experience and services

Public sector

Retail

Finances and insurance

ferroviari sector

Railway and Logistics

ICT

Cultural and creative industries

Multimedia

Kalium

Decide Madrid

AI & Big Data Congress

Highlighted projects

types eurecat

TYPES

Personal data anonymization and algorithmic discrimination detection technologies.

decode eurecat

Decode

New model for the treatment of online data in which citizens can decide what happens with their digital identity and with whom they share it.

Smooth

Platform to help micro, small and medium-sized companies (MSMEs) to validate their level of compliance with the European General Data Protection Regulation.

MoTiV

Research on VTT (value of travel time) by introducing and validating a conceptual framework for the estimation of VTT through a European-wide data collection.

Team

Cirus Iniesta

Director of the Big Data & Data Science Unit at Eurecat

Computer Engineer (UPF), MSc Economics with reference to Africa (SOAS, University of London) and postgraduate studies in Big Data and Analytics (UPC). From 2012 to 2015 he worked at the think tank Mo Ibrahim Foundation (London/Senegal), specializing in the generation of composite indices for the study of basic service provision in African macroeconomies. From 2015 to 2019 he worked as a data scientist in the mobile video game industry, where he became familiar in distributed computing environments. Since 2019 he works to Eurecat, first as a researcher and senior data scientist and currently as Director of the Big Data & Data Science (BD&DS) unit, integrated in the Digital Area. He has worked in areas of time series modeling and prediction as well as techniques related to natural language processing, both in understanding and generation.

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