Prof Jonathan Fieldsend
Professor in Computational Intelligence
Telephone: 01392 722090
Extension: (Streatham) 2090
Office: Innovation Centre Phase 1, Room 1
I am Professor of Computational Intelligence, and Academic Lead of the Optimisation Group in the Department of Computer Science.
I graduated with a BA in Economics from the University of Durham in 1998, an MSc in Computational Intelligence from the University of Plymouth in 1999 and a PhD in Computer Science from the University of Exeter in 2003. Following which I held postdoctoral research positions before starting as Lecturer at Exeter in 2006.
My research has been supported by a number of grants, with funders including EPSRC, Innovate UK, NERC, and industy. I am currently an Associate Editor of ACM Transactions on Evolutionary Learning and Optimization and IEEE Transactions on Evolutionary Computation, and on the Editorial Board of Complex and Intelligent Systems (Springer). I am a vice-chair of the IEEE Computational Intelligence Society Task Force on Data-Driven Evolutionary Optimization of Expensive Problems and also vice-chair of the IEEE Computational Intelligence Society Task Force on Multi-Modal Optmization. I was also co-Chair of the EMO Track at GECCO 2019 and GECCO 2020.
Most of my codebase relating to my recent publications is available on GitHub. Please access the repositories here.
Research and Professional Interests
My main areas of research are: developing multi-objective 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.
- Data-Driven Surrgate-Assited Fluid Dynamic Optimisation, which involved 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.
- MASS modelling and optimisation (with the MET office)
Current industry projects include:
- Calibration of digital twin models for buildings and road networks (with City Science and Hoare Lea),
- Bayesian optimisation for product design (with Hydro International)
- Computational modelling and optimisation of plasma processes (with Oxford Instruments Plasma Technology)
- Human centric buildings for a carbon neutral future (with City Science)
Citation stats: h-index: 23 and i10-index: 47 according to Google scholar.
I do not currently have any open posititions in my group.
I am coordinator of the following module:
ECMM427 Group Development Project
I also supervise on
ECM3401 Individual Literatue Review and Project
ECMM428 Individual Research 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.
Feb 2021 - Joined the Program Committee of the MCDM symposium at IEEE SSCI 2021
Feb 2021 - Joined the Program Commitee of IEEE CEC 2021
Feb 2021 - Appointed as an Associate Editor of IEEE Transactions on Evolutionary Computation
Dec 2020 - Joined the Program Comittee of GECCO 2021
Dec 2020 - SAEOpt Workshop confirmed for GECCO 2021, co-organising with Richard Everson (Exeter), Alma Rahat (Swansea), Yaochu Jin (Surrey) and Handing Wang (Xidian)
Dec 2020 - EAPwU Workshop confirmed for GECCO 2021, co-organising with Khulood Alyahya (Exeter), Tinkle Chugh (Exerter) and Juergen Branke (Warwick)
Dec 2020 - Competition on Niching Methods for Multimodal Optimization confirmed for GECCO 2021, co-organising with Michael Epitropakis (Lancaster), Xiaodong Li (RMIT) and Mike Preuss (Lieden)
Nov 2020 - Non-dominated Sorting on Performance Indicators for Evolutionary Many-objective Optimization, by Hao Wang, Chaoli Sun, Guochen Zhang, Jonathan Fieldsend and Yaochu Jin, accepted for publication in Information Sciences.
Qualifications: BA Economics (Dunelm), MSc Computational Intelligence (Plym), PhD Computer Science (Exon)
Professional memberships: MIEEE, FHEA
Patents: A method of selecting operational parameters in a communication network EP1730980 WO2005091948 GB2412275