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Xin Yao

Professor Xin Yao

Professor Xin Yao

Research Fellow

Interests and expertise (Subject groups)

Grants awarded

Foundations and Applications of Nature Inspired Computing Systems

Scheme: Wolfson Research Merit Awards

Organisation: University of Birmingham

Dates: Aug 2012-Aug 2017

Value: £50,000

Summary: Natural computation is the study of computational systems that use ideas and draw inspiration from natural systems, where a range of techniques and methods are studied for dealing with large, complex, uncertain and dynamic problems, in a distributed and decentralised fashion. So far my research has centred around evolutionary computation and ensemble learning. It has led to novel algorithms to solve effectively complex nonlinear problems with constraints, e.g., those problems occurred in software project scheduling and handover in a distributed smart camera network. Evolutionary computation techniques have also been used with success in knowledge discovery from noisy data in a changing environment. In particular, multi-objective learning has been shown to be able to produce highly competitive learners through simulated evolution and ensemble learning. There are many open research questions in natural computation to be answered, especially the foundations underlying different nature inspired systems. My future research focuses on two major issues. (a) What are most appropriate mathematical and computational frameworks for modelling natural systems such that we can gain deep understanding of such systems? (b) How and when can a nature inspired computing system outperform an existing system and why? Built upon this research and new understanding, novel nature inspired computing systems will be developed for tackling large and complex problems in dynamic and uncertain environments. Such problems include autonomous management of mobile communication networks, where nodes may be added or removed at any time and failures may happen at any node any time, optimisation of complex transportation networks consisting of different vehicles as well as people, self-learning of autonomous systems in an unknown environment, energy consumption monitoring and management in a modern city, etc.

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