1. Theories of Reasoning under Uncertainty, Uncertain Information Fusion, Multi-criteria Decision Making under Uncertainty:
This research is concerned with modelling, reasoning, and merging uncertain information from heterogeneous sources
in any intelligent systems (e.g., large sensor networks). We particularly focus on the Dempster-Shafer theory of Evidence
(belief function theory), possibility theory and possibilistic logic, and probability theory.
We research into
the appropriateness of modelling uncertain information using these formalisms, aggregation
approaches offered by them, and conflict/inconsistency analysis among multiple
piece of uncertain information within these theories. Recent work has advanced to handling ambiguous evidence in game theory for security
and multi-criteria decision making under uncertainty in complex systems.
2. Theoretical aspects of Merging/Revising Uncertain and Inconsistent Knowledgebases:
Our research includes developing fusion methods (merging operators) and algorithms for merging
multiple knowledgebases (maybe with constrains), especially, propositional and possibilistic knowledgebases,
stratified knowledgebases, imprecise probabilistic logic based knowledge bases,
and heterogeneous uncertain information. We also develop
revision strategies/operators for revising such knowledge/belief bases. Recent research has progressed to providing a toolkit for identifying minimal
inconsistent subsets and calculating
inconsistency values of knowledgbases or individual formulae in large scale knowledge bases. This research has also been extended to developing approaches for
detecting inconsistencies in probabilistic knowledge bases (learned by other machine learning systems) and
repairing such inconsistencies.
3. Data mining, large scale data analytics, anomaly/threats detection
Knowledge acquisition is expensive and often there is no expert around from whom
to elicit the knowledge. We study Machine Learning and Data Mining techniques to discover
knowledge from data that are easily comprehensible to humans.
Our earliest work was on developing algorithms for constructing Bayesian Networks from data.
Recent works in this area are strongly influenced by emerging real-world applications, including:
Design and develop anomaly detection algorithms for detecting abnormal
behaviors (anomalies) in physical access control environment under the context of security
within CSIT; develop graph-theory based algorithms for identifying exercise
patterns and influences among participants in events; and discover social connection
patterns from social networks.
Design and develop various data analytical approaches, in collaboration with
Belfast City Council, for analyzing data on Pollution, Waste disposal/treatment, Recycling; Anti-Social Behaviors, etc.
Design and develop real-time threats and anomaly prediction
algorithms with missing values in datasets, using knowledge discovered above,
to provide real-time situation awareness for decision support.
4. Intelligent Autonomous Systems and Event-reasoning based Situation Awareness:
Our research on theoretical research in uncertain information modelling and fusion, and knowledge evolution and inconsistency handling
have enabled us to:
Design and develop a multi-agent based event reasoning framework for correlating dispersed events detected from heterogeneous sources
in a distributed complex environment for achieving situation awareness. Applications include intelligent surveillance in cyber-physical systems,
smart homes, and intelligent energy and transport management in smart cities.
Design and develop intelligent autonomous systems
using multi-agent techniques for complex control problems and for designing collaborative (software) agents, or mixed teams of
multi-robots and human for working
together in complex environment.
Applications include search and rescue, services, complex industrial control problems,
and games for entertainment or education.
Weiru Liu and Henri Prade (Guest Editors): Special Issue of Fuzzy Sets and Systems 2013.
Weiru Liu (Guest Editor): Special Issue of International Journal of Approximate Reasoning, 2013.
Conference Chairs/Steering Committee member:
Program Co-Chair of the 7th International Conference on Scalable Uncertainty Management
(SUM'13), 16-18 September, 2013. Washington DC Area, USA.
Conference/Program Chair of the Eleventh European Conference on Symbolic and Quantitative Approaches to
Reasoning under Uncertainty
(ECSQARU'11). June 29the - July 1st, 2011.
Belfast, Northern Ireland, UK.