Prof Jonathan Fieldsend
Telephone: 01392 722090
Extension: (Streatham) 2090
Research and Professional Interests
My main areas of research are: developing multi-objective/non-traditional objective optimisation methods, multi-modal optimisation, optimisation with uncertainty, evolutionary approaches to learning, data visualisation, as well as the use of Bayesian classification/modelling techniques.
Previous industrial projects I've worked on include:
- Automatic Coverage and Capacity Optimisation for Next Generation Access Technology (with Motorola),
- Optimisation of Fraud Detection Software (with AI corp),
- Automated Multi-Objective Optimisation of Short Term Alert Safety Net Systems (with NATS)
- Multi-Objective Optimisation of Wireless Mesh Networks (including resource allocation, and interactive visualisation tools) with IMC group.
I am currently a co-investigator on the EPSRC funded project EP/M017915/1 "Data-Driven Surrgate-Assited Fluid Dynamic Optimisation", which involves collaboration with the UK Aerospace Technology Institute and QinetiQ on complex aerodynamic optimisation, with Hydro International on cyclone separation and with Ricardo on diesel particle tracking.
I am a member of the IEEE (Institute of Electrical and Electronics Engineers), the IEEE Computational Intelligence Society, the BCS, the ACM Special Interest Group on Genetic and Evolutionary Computation and a Fellow of the Higher Education Academy. I am a vice-chair of the IEEE Computational Intelligence Society Task Force on Data-Driven Evolutionary Optimization of Expensive Problems.
Citation stats: h-index: 21 and i10-index: 32 according to Google scholar.
I currently have a fully funded studentship (fees and stipend) for UK/EU candidates, jointly supervised with Dr Ozgur Akman, in the area of "Big Data Analytics: Visualising high-dimensional cost function landscapes". The full advert is here. Note the application deadline is 10th January 2018.
I graduated with a BA in Economics from the University of Durham in 1998, an M.Sc. in Computational Intelligence from the University of Plymouth in 1999 and a Ph.D. in Computer Science from the University of Exeter in 2003. I am currently an Associate Professor in Computational Intelligence, having previously held positions as a Research Fellow, Business Fellow, Lecturer and Senior Lecturer at Exeter.
I am currently employed on a flexible working contract (80%), and do not work on Mondays - when I take care of my young family.
Some of my codebase relating to my recent publications is available on GitHub. Please access the repositories here.
I am coordinator of the following module:
ECMM427 Group Development Project
I also supervise on
ECM3401 Individual Literatue Review and Project
I am interested in supervising postgraduate students with projects in the broad area of Nature Inspired Computation and Machine Learning. Please apply via the university online portal.
I have reviewed for a number of journals in my field, including:
- IEEE Transactions on Evolutionary Computation,
- Evolutionary Computation Journal,
- IEEE Transactions on Systems, Man and Cybernetics- Part B,
- IEEE Transactions on Neural Networks and Learning Systems,
- IEEE Transactions on Medical Imaging,
- IEEE Transactions on Automation Science and Engineering,
- Swarm Intelligence,
- Knowledge and Information Systems,
- Pattern Analysis and Applications,
- International Journal of Forecasting,
- International Journal of Parallel, Emergent and Distributed Systems,
- European Journal of Operations Research,
- Journal of Mathematical Modelling and Algorithms,
- Computational Optimization and Applications,
- Complex and Intelligent Systems.
I am also on the editorial board of Complex and Intelligent Systems (Springer), and regularly review for the main conferences in my field (e.g. GECCO, IEEE CEC, EMO, PPSN, IEEE SSCI, UKCI, etc.).
I have also reviewed grant applications for EPSRC.
Qualifications: BA Economics (Dunelm), MSc Computational Intelligence (Plym), PhD Computer Science (Exon)
Professional memberships: MIEEE, FHEA, MBCS
Patents: A method of selecting operational parameters in a communication network EP1730980 WO2005091948 GB2412275