Area of Study / Keywords
Computer Engineering Software Engineering and Intelligent Systems
The general research interests lie in the realm of Computational Intelligence (CI), bioinformatics, and Granular Computing regarded as a recent development in the design and analysis of intelligent and human-centric systems. CI hinges on a synergistic interaction of the leading information technologies such as fuzzy sets, neural networks and evolutionary computing. The key research activities focus on the following pursuits:
- The development of an array of architectures of CI systems exploiting an important synergistic interaction between fuzzy sets (and granular computing, in general), neurocomputing and evolutionary methods. The focal point of research deals with neurofuzzy systems, their learning and interpretation of the resulting constructs.
- Development of features of human-centricity of intelligent systems (which in turn invoke detailed studies on mechanisms of collaboration, filtering, and relevance feedback)
- Applications of CI to several specific areas including face recognition, biometrics, software engineering (software measures, software cost estimation, software product lines), data mining and knowledge discovery
- Intensive numeric experimentation with the variety of CI models with emphasis on the scalability analysis of the models (dimensionality reduction)
- Event detection in streams of data for data mining
The current research pursuits concentrate on the developments of distributed and collaborative fuzzy modelling realized in the setting of Computational Intelligence and Granular Computing. This comes as a new and very much unexplored territory whose importance and relevance is growing given the fact of the distributed nature of a large number of systems available these days. Here several fundamental pursuits are sought:
- Investigation of various aspects of collaboration and knowledge sharing realized in presence of technical constraints and aspects of privacy and security of available information
- Algorithms of collaborative clustering as a vehicle of structure determination and structure sharing
- Studies on the role of information granularity versus the computational and functional constraints of fuzzy modelling
- Design of mechanisms of knowledge sharing
- Emergence of higher order granular constructs
From software requirements specification to software testing. Risk analysis and metrics for software testing. Software testing process, including test planning, design, implementation, execution, and evaluation. Test design via white box and black box approaches; coverage-based testing techniques. Unit, integration, and system testing. Acceptance tests. Software maintenance and regression testing. Prerequisite: CMPUT 275. Credit may be obtained in only one of CMPE 320 or ECE 322.
Developments in human-centric systems. Fuzzy sets and information granulation. Computing with fuzzy sets: logic operators, mapping, fuzzy relational calculus. Fuzzy models and rule-based models. Fuzzy neural networks. Fuzzy clustering and unsupervised learning.