I am a final year doctoral student and member of the Information Systems Group
led by Prof. Ian Horrocks. During my DPhil, I worked on knowledge
representation and reasoning formalisms modelling non-tree structures, such as complex
biochemical objects. Specifically, I built a theoretical and practical
logic-based framework for the classification of graph-shaped objects based on their structural properties. In the context
of this framework, I researched extensions of datalog rules with existentials in the head
and nonmonotonic negation in the body and their application to automatically building taxonomies of manually
curated knowledge bases.
Prior to that, I completed an MSc Computer Science degree in the Department of Computer Science, University of Oxford; for my MSc project and under the supervision of Dr. Yevgeny Kazakov and Prof. Ian Horrocks I outlined polynomiality conditions for the lightweight description logic EL when extended with numerical datatypes.
For my first degree, I studied electrical and computer engineering in National Technical University of Athens. In my undergrad project and under the supervision of Dr. Giorgos Stamou, I explored methods for connecting databases and ontological knowledge under the presence of uncertainty. In particular, I developed a java tool to convert database tuples into fuzzy OWL assertions according to user-defined membership functions.
Concrete Results on Abstract Rules
Markus Krötzsch‚ Despoina Magka and Ian Horrocks
In Proceedings of the 12th International Conference on Logic Programming and Nonmonotonic Reasoning. September, 2013.
Computing Stable Models for Nonmonotonic Existential Rules
Despoina Magka‚ Markus Krötzsch and Ian Horrocks
In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013). August, 2013.
Acyclicity Notions for Existential Rules and Their Application to Query Answering in Ontologies
Bernardo Cuenca Grau‚ Ian Horrocks‚ Markus Krötzsch‚ Clemens Kupke‚ Despoina Magka‚ Boris Motik and Zhe Wang
In Journal of Artificial Intelligence Research (JAIR). Vol. 47. 2013.