Web and social media mining

The large-scale availability of user-generated content in social media platforms has opened up new possibilities for studying and understanding real-world phenomena, trends and events. Social media is a highly heterogeneous source of data that provides real-time information in specific areas of interest, which can assist public safety through the monitoring…
Read More...

Multimedia retrieval

Big Data Collections (e.g. Earth Observation data, social media streams, large video collections, etc.) are characterised by large volumes, velocity and variety, due to their high heterogeneous nature and timeliness. Multimedia retrieval requires efficient indexing of the available raw data and extracted metadata, such as concepts, visual features, textual features…
Read More...

Computer vision

Digital images and video footages comprise one of the core data types for human-machine interaction and visual understanding in general. Human perception along with the human logic are the most attractive capabilities of the human species that the research community strives to mimic. Except the relevant perception models, the community…
Read More...

Multimodal Data Fusion

A key requirement in multimodal domains is the ability to integrate the different pieces of information, so as to derive high-level interpretations. More precisely, in such environments, information is typically collected from multiple sources and complementary modalities, such as from multimedia streams (e.g. using video analysis and speech recognition), lifestyle…
Read More...

Big Data processing and analytics

Spatial, textual and visual data are ubiquitous and are massively generated by cameras, satellites, sensors and humans. Clustering large and semi-structured data is a very popular pattern recognition problem in the Big Data era, that aims to support data management and grouping into topics. Our research focus is to identify…
Read More...

Multimodal analytics based on Artificial Intelligence

Artificial intelligence (AI) technologies, and in particular the deep learning paradigm, are advancing at an astounding pace and appear to have the potential to significantly enhance the capabilities in a wide range of applications. Multimodal analytics aim to uncover the structure underlying the multimodal information of interest and organise it…
Read More...

Knowledge Representation and Reasoning

The Semantic Web technologies provide the means and tools to unanimously represent the meaning of Web entities and their relations to one another, in a machine-interpretable manner. While modelling and managing knowledge for web entities has long ago been established, the Semantic Web technologies also show great potential in other…
Read More...

Decision support and visual analytics

This research direction includes a unified multi-layer framework that encapsulates machine learning techniques in a specific assessment process for analysing and fusing dynamically heterogeneous information obtained from various sources. For example, in the disaster management sector, the solutions that we design and develop in the research direction aim to classify…
Read More...