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Tomas Pariente Lobo

AI and Big Data: Getting value and intelligence from data


We focus on the application of AI and Big Data technologies to real scenarios where the innovation is fundamental to contribute to a data-driven society powered by the massive amounts of data available today through multiple devices and locations such as mobiles, homes, cities, cars, etc. These set of technologies pose not only technical but also societal and ethical issues.

  • Artificial Intelligence: Machine Learning and Deep Learning to enable multiple applications to real-world scenarios.
  • Big Data: Covering most of the technical aspects of the Data Value Chain to get value from the data. The use of blockchain to enable secure data sharing is one of our key research lines.
  • Semantics: Application of Knowledge Graphs and Linked Data as enablers for AI.

Our main vision is to carry out research on AI-guided by strong ethical principles, to avoid the misuse of AI and Big Data, and ensure data privacy and auditability while enabling the use of the technology. In this sense, Blockchain technology is also being integrated as an enabler to break data silos.

From the technical perspective, the Lab is developing services to easily define and deploy big data and machine learning frameworks and algorithms on demand (especially useful for data scientist and SMEs), with the combination of cloud and edge analytics, as well as Big Data Benchmarking solutions which recommend and deploy the right tool for benchmarking their applications and Big Data services.


Our Lab provides a unique point of contact with the R&D carried out in the Big Data and AI fields in Europe through our participation in the Big Data Value Association and lighthouse AI projects, in particular by developing assets that allow deploying and configure Big Data frameworks, ML libraries, and algorithms; analyze social networks; search and recommend Big Data tools; and enable data sharing using a Blockchain approach.

Knowledge in these fields makes the Lab a key driver in the research of new ways to empower companies in their digital transformation while keeping ethical values at their forefront.



A cyberphysical social network using robot friends
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Using robots to increase the number of older adults who engage in a regular and sustained physical activity.


Support the Big Data Value PPP in realizing a vibrant data-driven EU economy and contribute to the implementation of the PPP.


Big Data for Medical Analytics
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Enhancing patient outcomes and increase productivity in the health sector by applying Big Data technologies to complex datasets while ensuring security and privacy of personal data.


API-ecosystem for cross-sectorial exchange of 3D personal data
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Aims at fostering exchange the of 3D data assets from two sectors, by adapting and creating tools to allow secure exchange of information between data owners, companies and subjects (patients and customers).


Collective wisdom driving public health policies
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Integration of high volumes of health-related heterogeneous data from multiple sources with the aim of supporting policy making decisions.



Evidence Based Big Data Benchmarking to Improve Business Performance
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Design of a benchmarking process helping European organizations developing Big Data Technologies to reach for excellence and improve their business performance.


Making transport smarter, leveraging the human factor
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Methods to perform cross-sectoral streaming Big Data integration including geographic, transport, meteorological, cross domain and news data, while capitalizing on human feedback channels.


Trustworthy model-aware analytics data platform
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Aims at overcoming some major hurdles that until now have prevented many European companies from reaping the full benefits of Big Data Analytics.