Here you can see my current activities:
http://personalpages.manchester.ac.uk/postgrad/eleni.mikroyannidi/
Summary
Eleni Mikroyannidi is currently working for the CASPAR project as a Research Assistant in the School of Music and Computing, University of Leeds. She has acquired a BEng in Electrical and Computer Engineering from the Electrical and Computer Engineering department, University of Patras and an MSc in Advanced Computer Science from the School of Computer Science, University of Manchester. She is interested in fields related to the Semantic Web area, such as manipulation of ontology models, OWL reasoning and machine learning techniques.
Research Interests
- Ontology models
- Data mining systems
- Human Computer Interaction
- Computer Supported Collaborative Learning (CSCL)
- Web technologies
Research Experience
MSc Dissertation: "Abstracting and Generalizing a Large Anatomy Ontology". The Foundational Model of Anatomy (FMA) is an ontology model with sheer size, consisting of approximately 65,000 concepts and describes the human anatomy in high detail. The purpose of the dissertation was the development of an abstraction methodology for the elimination of the repetitive information in order to decrease the number of concepts of the ontology and make it more efficient.
BEng dissertation: “Collaborative processes analysis with the use of Machine Learning Techniques”. The subject was the analysis of the network-mediated synchronous collaborative activities that are created during the use of computer supported collaborative work (CSCW) tools. Using machine learning methods, a model was trained to be able to classify rich set of examples of collaborative situations that have been evaluated manually in terms of a rating scheme for assessing the collaboration quality.
BEng dissertation: “Collaborative processes analysis with the use of Machine Learning Techniques”. The subject was the analysis of the network-mediated synchronous collaborative activities that are created during the use of computer supported collaborative work (CSCW) tools. Using machine learning methods, a model was trained to be able to classify rich set of examples of collaborative situations that have been evaluated manually in terms of a rating scheme for assessing the collaboration quality.
Publications
- Eleni Mikroyannidi, Alan Rector, Robert Stevens, "Abstracting and Generalising the Foundational Model Anatomy (FMA) Ontology" in Proceedings of the Bio-Ontologies 2009 Conference, Stockholm, June 2009.
- Kia Ng, Eleni Mikroyannidi, Bee Ong, David Giaretta, "An Ontology based Framework for the Preservation of Interactive Multimedia Performances" in Proceedings of the 5th IEEE International Conference on e-Science 2009, Oxford, UK.
- Kia Ng, Eleni Mikroyannidi, Bee Ong, Nicolas Esposito and David Giaretta, "Interactive Multimedia Systems for Technology-Enhanced Learning and Preservation" in Proceedings of the 15th International Conference on Distributed Multimedia Systems 2009, San Francisco, September 2009.
- G. Kahrimanis, E. Mikroyannidi, N. Avouris, “Assessing the Quality of Synchronous Network Learning Activities using Machine Learning Techniques” in Proceedings of Networked Learning Conference, Halkidiki, May 2008.
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