Dr Andrew Chipperfield

Andrew Chipperfield graduated with a BSc(Hons) in Computer Systems Engineering from University College of North Wales, Bangor, in 1989. In 1995 he obtained his PhD on computer aided control systems design in the Department of Automatic Control and Systems at the University of Sheffield as a research assistant. After spending three years as a research fellow in the Rolls Royce University Technology Centre for Systems and Control he was appointed lecturer in aerospace and control engineering. In 2002 he joined Southampton as a senior lecturer in computational methods.

His research interests are broadly in the fields of applying modelling, optimisation and control to real-world problems. An early example being the creation of the Genetic Algorithm Toolbox for Matlab which has been in use at 500+ industrial and academic sites worldwide, most notably helping NASA reduce the landing footprint of the Mars Pathfinder. In particular, multiobjective optimization techniques developed with Fleming (Sheffield) have been successfully applied to a wide range of problem domains from drug discovery (GlaxoSmithKline) and process scheduling (Beetson Clark) to system identification and control system optimization (Rolls Royce, BAE Systems, QinetiQ, DSTL). Previous research projects have include life-cycle cost modelling for UAV design using multiple simulation and modelling strategies and the use of mathematical modelling in large-scale data management for health monitoring and prognostics in helicopter fleet management (GE Aviation). Other collaborations have included the design of controllers for solar-thermal power generation (Tsang and Man, HK City University), optimisation in robust control (Whidborne, Cranfield) [19] and the control of novel agile UAVs (VTOL Technologies and MoD).

His current research is primarily focused on applying these systems engineering techniques to problems in biomedical and clinical science. He works closely with colleagues in medicine in Southampton and elsewhere and focuses on diabetes, metabolic syndrome and obesity. This work has been supported by EPSRC, Diabetes UK and industrial sponsorship.