research


the goal of my research activities is to develop methods and techniques for modeling data and knowledge, as well as design systems which possess abilities to imitate different aspects of human behavior

I focus on developing more human-aware and human-like systems via combining:

  • elements of Computational Intelligence - granular (fuzzy) computing, neuro computing, and evolutionary computing - able to capture relationships between pieces of data and knowledge, as well as mimic human ways of reasoning;
    with
  • techniques capable of dealing with uncertainty - possibility theory, probability theory, Dempster-Shafer's evidence theory;
    and with
  • Semantic Web based knowledge representation forms, especially Resource Description Framework (RDF)
I am also interested in mathematical theories, in particular, the category theory and type theory, which can be applied for representing and reasoning about knowledge; my intention is to develop a framework based on these approaches for constructing intelligent and human-centric systems


the following research topics are of interest for me:

knowledge extraction and knowledge representation
methods of fuzzy, neurofuzzy and evolutionary computing used for discovering and representing knowledge; category theory applied for constructing novel relations between pieces of information; RDF triples and ontology utilized as knowledge representation forms

semantic-based intelligent systems
RDF and ontology used for representing information and knowledge, reasoning engines utilized to provide more human-like outcomes; applications to computing with words, semantic web, and information analysis systems; automatic construction of concepts; elements of fuzziness applied to analysis of social networks

decision support
different models representing knowledge used to build systems supporting decision-making processes; integrating uncertainty with decision support systems - techniques coming from probability theory (Bayesian networks), Dempster-Shafer theory, and related to fuzzy impression; construction of decision support systems based on multiple models; multiple practical applications including design and development of recommender systems

software quality and maintenance
development - using above mentioned methods and techniques - of models for estimation and prediction of quality and maintainability of software components


ieee Computational Intelligence Society task force:

upcoming events