We are recruiting (Lecturers, Senior Lecturers, Readers) with the deadline of the first
phrase recruitment
as 12th January 2013.
Applications will still be processed after this first phrase deadline, until all posts are filled.
Please visit Jobs details
for on-line application. Or alternatively, please get in touch with us if you are interested to find out more.
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.
Member of the Ecsqaru Permanent Committee (ecsqaru.org)
Member of the Steering Committee of Belief Functions Series
(BELIEF)
1. Theories of Reasoning under Uncertainty, Uncertain Information Fusion, Conflict Analysis:
This research is concerned with modelling and merging uncertain information
in any intelligent systems. 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, as well as conflict/inconsistency analysis among multiple
piece of uncertain information within these theories.
2. Theoretical aspects of Merging/Revising Uncertain/Inconsistent Knowledgebases:
Our research includes developing fusion methods (merging operators) and algorithms for merging
multiple knowledgebases (maybe with constrains), especially, possibilistic knowledgebases,
stratified knowledgebases, imprecise probabilistic logic based knowledge bases,
and heterogeneous uncertain information. We are also interested in developing
revision strategies/operators for revising above mentioned knowledge/belief bases.
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 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 develop 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,
and 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. Applications with our theoretical studies:
Numeric-based combination approaches to sensor data fusion in general, multiple uncertain events
fusion in surveillance, uncertain activities fusion
in smart homes, combination of normal distributions with missing data in
clinical trials,
and the combination of uncertain mappings from multiple ontology mapping
algorithms etc.
Logic-based merging approaches to inconsistent requirements fusion in
requirements engineering, inconsistency handling in description logic through merging
and revision, modelling
and merging XML documents with uncertain information, and merging and revision of
imprecise probabilistic knowledge for substrates prediction.
New:
PACES Providing Autonomous Capabilities for Evolving SCADA (EPSRC 2012-2015), PI
(In
collaboration with Prof Lluis Godo and Prof Carles Sierra at IIIA in Barcelona)
New:
ARIES Accelerated Real-Time Information Extraction System (EPSRC 2012-2013),
Co-I
New: TEI@I Framework for Forecasting and Decision Making
(The Royal Academy of Engineering 2012-2013), PI
(In collaboration with Prof Gang Xie and Prof Xiaoguang Yang at
Chinese Academy of Sciences, China)
