Dr Ben Azvine
Industrial Applications of Intelligent SystemsAbstract
The dream of building intelligent machines has been with man for decades. Much has been discussed and written on the impacts of machine intelligence on human life, and some of man's wishes and fears have inspired science fiction movies in which the bright and dark sides of having around us artificial systems with more intelligent than humans have been shown. Nevertheless, research in intelligent systems has led to significant progress in understanding the nature of human decision making with significant implications on automation of manual tasks within industry. In this talk I'll focus on a number of case studies developed within BT that incorporate the results of intelligent systems research and describe their benefits. The talk will include examples from mobile workforce management, intelligent information management, data mining and customer relationship management (CRM).
Ben Azvine holds a BSc in Mechanical Engineering, an MSc in Control Engineering, a PhD in Intelligent Control Systems from Manchester University and an MBA from Imperial College, London. Having held research fellowship and lectureship posts in several universities, he joined BT in 1995 to set up a research programme to develop and exploit soft computing and computational intelligence techniques within BT. Since then he has held senior, principal and chief research scientist posts at Adastral Park where he currently leads the computational intelligence research group. He has edited two books and published more than 100 scientific articles. He is an inventor on 30 patents, has won two BCS gold medals, holds a visiting professorship at Bournemouth University, and visiting fellowships at Bristol and Cranfield Universities, and was the cochairman of the European Network of Excellence for Uncertainty Management Techniques. His current research interests include the application of soft computing to intelligent data analysis and intelligent information management. His current projects include building a soft computing platform for intelligent data analysis, developing a methodology for customer satisfaction modelling, developing decision support tools for universal service management, building intelligent information retrieval capability for future contact centres and research into automatic identification of abnormal patterns from sensor data for health care.