My research interests lie in intelligent and adaptive systems, agents and multi-agent systems (their theoretical foundations and practical applications), data exploration, analysing and modelling complex data (structured and unstructured) and Big data.
In particular, I have been working on a range of topics:
· Data exploration; analysing and modelling complex data; Big data; analysis and modelling of structured and unstructured data
· Formal theories of agents and multi-agent systems; BDI agents
· Cognitive agents; knowledge and belief; self-reference
· Software engineering methodologies for agents and multi-agent systems
· Social dynamics; regulation of agent societies; roles and power; institutions
· Market mechanisms; negotiation protocols; strategic interaction; supply chain management
· Machine learning; modelling opponents; learning behaviours from data
· Individual and collective user profiles; profile adaptation; contextualised profiles
· Recommender systems; collaborative filtering; reputation systems
· Web search assistants
· Serious games for education and learning; collaborative learning
· Self-organisation; team formation
· Semantic matching; resource search; cloud computing resource allocation
· Trust in agent societies; trust mechanisms; trust in decision making
A significant aspect of my work relates to data exploration and in particular analysing and modelling complex data. Data can be structured (numerical such as prices) or unstructured (text, documents, user interests) and can also be Big Data. A number of techniques have been used in analysing and learning from data including statistical and machine learning techniques as well as other techniques that are not applicable to well-structured data. Modelling data and obtaining predictive insight is a key area of research and we have been using agent-based simulations and multi-agent systems to create complex models of systems.
I am currently involved in a number of projects, including:
· Innovative tools to enable exploration of complex and specialised data sets
· Data analytics driven by ontologies
I have been supervising PhD students in a range of topics in the areas listed above. I am currently supervising students in recommendation technologies, semantic information extraction and user profiling, self-organisation in complex systems and learning from and modelling complex and Big Data. If you are interested in pursuing your PhD studies in any of the areas listed above, you can contact me by email.
I am also very much interested in pedagogical research and in particular game-based learning, interactive learning, collaborative-based learning and the use of technology in general to both support and enhance the students' learning experience. More information about my learning and teaching approaches and interests can be found in the Learning and Teaching section of my site.
A talk delivered as part of TEDxUniversityofEssex
© Maria Fasli 2015