Development and Application of Soft Computing Models

 

Prof Chee-Peng Lim

Institute for Intelligent Systems Research and Innovation

Deakin University, Australia

 

 

Abstract

Soft computing is a broad discipline that encompasses a variety of methodologies inspired by human and/or animal intelligence.  In this talk, the design and development of several soft computing models and their use for intelligent data analytics is described.  The underlying computational frameworks exploit the capabilities of individual and hybrid data-based soft computing models, which include artificial neural networks, fuzzy systems, and evolutionary algorithms.  Ensemble architectures are leveraged to further enhance robustness and efficacy of the resulting frameworks.  In addition, application of the resulting soft computing models with intelligent reasoning and inference capabilities to a variety of real-world medical and industrial problems is demonstrated.

 

Biography

Chee Peng Lim received his Ph.D. degree from the Department of Automatic Control and Systems Engineering, The University of Sheffield, UK, in 1997. His research focuses on intelligent computational systems for pattern classification, data analytics, and decision support.  He has authored/co-authored over 500 papers, and received 8 best paper awards in international conferences.  He has also won several prestigious fellowships for international collaboration, which include the Australia-India Senior Visiting Fellowship (by Australian Academy of Science), Australia-Japan Emerging Research Leaders Exchange Program (by Australian Academy of Technology and Engineering), Commonwealth Fellowship (at University of Cambridge), Fulbright Scholarship (at University of California, Berkeley), and Visiting Scientists Program of the US Office of Naval Research Global (at Harvard University and Stanford University).