› Research interests

  • Knowledge Discovery in Data – KDD, Data Mining: Classification, cluster analysis, pattern representation and management, machine learning
  • Database & DataWarehouse Management: query processing and optimization, spatial / spatiotemporal database management
  • Geographical / Mobile Information Systems: Location-based systems and services in mobile environments

  • › Conference Organization

    ECML PKDD 2011

    Member of the organizing committee of the "European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)" in Athens, Greece, September 5-9, 2011.

    BMDA 2018

    Co-organizer of the "Big Mobility Data Analytics (BMDA@EDBT'18)" workshop in EDBT 2018 21st International Conference on Extending Database Technology, Vienna, Austria, March 26-29, 2018.

    DMKD 2009

    Stream co-organizer with title "Data Mining and Knowledge Discovery" in EURO 2009 23rd European Conference on Operational Research, Bonn, Germany, July 5-8, 2009.

    DMGI 2008

    Session co-chair with title "Data Mining and Geographic Information" in EEEE 2008 20th Hellenic Conference on Operational Research, Spetses, Greece, June, 2008.

    › Projects


    "Multiple Aspects Trajectory Management and Analysis" Horizon 2020 / ICT Programme Marie Skłodowska-Curie Research and Innovation Staff Exchange (MSCA-RISE).
    Abstract: An ever-increasing number of diverse, real-life applications, ranging from mobile phone calls to social media and land, sea, and air surveillance systems, produce massive amounts of spatio-temporal data representing trajectories of moving objects. Trajectories, commonly represented by sequences of timestamps and position coordinates, thanks to the high availability of contextual and semantic-rich data can be enriched and are evolving to more comprehensive and semantically significant objects. We envision holistic trajectories, meaning trajectories characterized by the fact that the spatio-temporal and semantic aspects are intimately correlated and should be considered as a whole. However current state of art does not provide management and analysis methods "ready for use" for these multiple aspects trajectories.

    Track & Know

    "Big Data for Mobility Tracking Knowledge Extraction in Urban Areas" Horizon 2020 / ICT Programme.
    Abstract: Track&Know will research, develop and exploit a new software framework that aims at increasing the efficiency of Big Data applications in the transport, mobility, motor insurance and health sectors. Stemming from industrial cases, Track&Know will develop user friendly toolboxes that will be readily applicable in the addressed markets, and will be also investigated in additional domains through liaison activities with running ICT-15 Lighthouse projects. Track&Know integrates multidisciplinary research teams from Mobility Data management, Complex Event Recognition, Geospatial Modelling, Complex Network Analysis, Transportation Engineering and Visual Analytics to develop new models and applications. Track&Know recognizes that Big Data penetration is not adequately developed in niche markets outside the traditional verticals (e.g. Finance) and so the Track&Know Toolboxes will be demonstrated in three real-world Pilots using datasets from niche market scenarios to validate efficiency improvements. Performance and impact benchmarks are elaborated and will be documented during pilots deployment. The Track&Know consortium is composed by complementary partners, coming from addressed research, technological and commercial domains, that have a proven track record of high quality research capacity. Thus, the carefully structured workplan, embodies a holistic approach towards meeting the Track&Know objectives and delivering market-relevant outcomes of significant exploitation potential.


    "Big Data Analytics for Time Critical Mobility Forecasting" H2020 research and innovation programme.
    Abstract: datACRON advances the management and integrated exploitation of voluminous and heterogeneous data-at-rest (archival data) and data-in-motion (streaming data) sources, so as to significantly advance the capacities of systems to promote safety and effectiveness of critical operations for large numbers of moving entities in large geographical areas.


    "Data-Driven Aircraft Trajectory Prediction Research" H2020-SESAR-2015-1, Type of Action: SESAR-RIA.
    Abstract: DART will explore the applicability of a collection of data mining, machine learning and agent-based models and algorithms to derive a data-driven trajectory prediction capability. Those algorithms are expected to provide increased levels of accuracy while considering ATM network effects in the prediction process, which have been rarely introduced by current state-of-the art solutions.


    Abstract: The goal of the AMINESS project is to promote shipping safety in the Aegean Sea through a web portal offering different levels of access to relevant stakeholders such as ship owners, policy makers, the scientific community and the general public.


    "Foundations for personalized Cooperative Information Ecosystems" Thalis, 2012-2015.
    Abstract: The aim of EICOS is to provide the methodology, the theoretical and modeling foundations as well as the algorithmic techniques and the necessary software architecture that will facilitate the personalization, integration, and evolution management facilities for information ecosystems that operate over a decentralized infrastructure for a large variety of data types.


    "SEmantic Enrichment of trajectory Knowledge discovery" PEOPLE – IRSES 2011.
    Abstract: A flood of data pertinent to moving objects is available today, and will be more in the near future, particularly due to the automated collection of data from personal devices such as mobile phones and other location-aware devices. Such wealth of data, referenced both in space and time, may enable novel classes of applications of high societal and economic impact, provided that the discovery of consumable and concise knowledge out of these raw data is made possible.


    "DATA science for SIMulating the era of electric vehicles" FP7, 2011-2014.
    Abstract: DATA SIM aims at providing an entirely new and highly detailed spatial-temporal microsimulation methodology for human mobility, grounded on massive amounts of Big data of various types and from various sources, e.g. GPS, mobile phones and social networking sites, with the goal to forecast the nation-wide consequences.


    "Mobility, Data Mining, and Privacy" EU FET-OPEN 2009-2012. The Future and Emerging Technologies Open Scheme. Project funded by the European Commission.
    Abstract: MODAP aims to create a platform for technical as well as non-technical people who are interested in mobility data mining together with privacy issues.


    "MOVE: Knowledge Discovery from Moving Objects" MOVE is an Action of the COST Programme (European Cooperation in Science and Technology) funded in the period of 11/2009 to 10/2013 by the European Science Foundation, allowing the coordination of nationally-funded research on a European level.
    Abstract: The main objective of MOVE (COST Action IC0903) is to develop improved methods for knowledge extraction from massive amounts of data about moving objects. MOVE aims to build a network for collaboration that leads to the improvement of ICT methods for knowledge extraction from massive amounts of data about moving objects. This knowledge is essential to substantiate decision making in public and private sectors. Moving object data typically include trajectories of concrete objects (e.g. humans, vehicles, animals, and goods), as well as trajectories of abstract concepts (e.g. spreading diseases). While movement records are nowadays generated in huge volumes, methods for extracting useful information are still immature, due to fragmentation of research and lack of comprehensiveness from monodisciplinary approaches. Overcoming these limitations calls for COST-like networking.


    "Geographic Privacy-aware Knowledge Discovery and Delivery" FP6-14915 IST/FET Project funded by the European Commission.
    Abstract: The general goal of the GeoPKDD project is to develop theory, techniques and systems for knowledge discovery and delivery, based on new automated privacy-preserving methods for extracting user-consumable forms of knowledge from large amounts of raw data referenced in space and in time.


    "Spatio-temporal Data and Knowledge Management in Expert Virtual Environments " Pythagoras EPEAEK II Programme of the Greek Ministry of National Education and Religious Affairs, co-funded by the European Union.
    Abstract: Investigation of novel techniques for the representation and management of spatio-temporal data and knowledge with applications in intelligent virtual environments, i.e. realistic synthetic worlds "inhabited" by graphical intelligent and interactive agents. (Joint research with Knowledge Engineering Lab @UNIPI)


    "Management of spatiotemporal and semantic data for the documentation of historical information", founded by the Greek Ministry of Development, General Secretariat for Research and Technology, co-funded by the European Union.
    Abstract: Diachoron aims at the development of a model to represent the spatiotemporal developments of various types of historical information. More specifically, it focuses at the modeling of the borders (e.g. phycical, administrative and/or imaginable -- coastlines, abuttals, proliferation of various phenomenon -- and of their respective mutation during certain time intervals. The whole process is assisted by integrating various types of metadata related to the documentation of the spatio-temporal alterations.


    "Ontology-based construction and management of metadata for the intelligent search in document and imagery collections", founded by the Operational Programme Information Society of the Greek Ministry of Development, General Secretariat for Research and Technology, co-funded by the European Union.
    Abstract: The core objective of MetaOn is to construct and integrate semantically rich metadata collections extracted from documents images and linguistic resources, to facilitate intelligent search and analysis. The MetaOn framework involves, ontology-based information extraction and data mining, semiautomatic construction of domain specific ontologies, content-based image indexing and retrieval, and metadata management.


    "Management of Moving Objects and the World Wide Web, Archimedes EPEAEK II Programme of the Greek Ministry of National Education and Religious Affairs, co-funded by the European Union.
    Abstract: Development of technologies and a prototype, Web-based data management system for moving object applications, including Location-based Services (LBS). (Joint research with Database group @TEI Thessaloniki)