Technological groups
CAKT | Content Analysis and Knowledge Technologies
The group brings together researchers and developers covering a variety of domains related to Natural Language Processing, Data Mining, Machine Learning, Knowledge Representation and Visualization under a common aim. The aim is to develop top-notch, scalable and widely adoptable methods and system solutions for multi-modal content analysis, knowledge representation and management.
CER | Complex Event Recognition Group
The group has been developing formal computational methods which take as input streams of low-level events, e.g. sensor-based events, such as a change in temperature, and combine them to infer complex high-level events of interest, such as the start of a fire incident or a fault in the cooling system of a vehicle.
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DEG | Data Engineering Group
The group has carried out research along three closely related axes: (1) The automated homogenization and integration of distributed databases, especially in the Semantic Web context;
(2) Distributed data, Big data and private and sensitive data management & processing; (3) Programming languages for processing workflows over big volumes of data or high-speed data streams.
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RoboSKEL | Robotics Activity
Roboskel’s origins are traced to the involvement of SKEL in the robotics project Indigo, transferring, adapting, and extending SKEL’s personalization technologies in the domain of Human-Robot Interaction. Over the years, this has led to our formulating and pursuing our Consumer Robotics vision of HRI that can make using robots as easy as it needs to be for robots to be useful in our everyday life.
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DICE | Artificial Intelligence Center of Excellence on Document Intelligence
DICE is an AI Centre of Excellence focusing on document intelligence. Its purpose is to develop novel AI methods for use cases related to business documents. The aspiration for this centre is to become a reference centre when it comes to AI for business documents. Visit the [website]
ID-IS | Intelligent Data-Intensive Systems
ID-IS undertakes research that lies in the wider area of AI, focusing on the use of intelligent e-infrastructures, deep learning, data-intensive computing or big data solutions in order to support cross-disciplinary scientific applications and research.
application teams
BioHIT | Biomedical and Health Informatics Team
BioHIT is a team that focuses on machine learning, data mining, knowledge representation and visualisation, as well as combination of heterogeneous data resources with already established knowledge. Advanced methods from these areas are applied to biomedical and health data and corresponding infrastructure is developed and maintained.
> Visit BioHIT’s website
Artifact | Artificial Intelligence for Culture
The Artifact team connects AI with culture through projects that combine digitisation technology with cultural practices.
AHEDD | the Attica Digital innovation Hub for the Economy of Data & Devices
ahedd Digital Innovation Hub is an ecosystem of research & corporate entities that have exceptional know-how in offering digital transformation & innovation solutions.
> Visit ahedd’s website