Dr Jethro Shell

Job: VC2020 Senior Lecturer

Faculty: Technology

School/department: School of Computer Science and Informatics

Research group(s): Centre for Computational Intelligence (CCI)

Address: De Montfort University, The Gateway, Leicester, LE1 9BH, UK

T: 44 (0)116 207 8520

E: jethros@dmu.ac.uk

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Personal profile

Whilst working for Panasonic Computer Products (Europe), Dr Shell completed a part time MSc in Information Technology at De Montfort University, finishing his studies in 2008. Following a 10 year career with Panasonic, he left industry to return to academia completing a PhD at De Montfort University. The focus of his PhD was on sparse data environments where the ability to gain labelled data is initially either extremely difficult or impossible. Environments such as extremely remote locations, ad-hoc structures or user groups that are very specific. These environments often also produce uncertain and vague data. To address these issues he constructed a framework that combined a fuzzy logic representation of the data with a transductive transfer learning approach.

Dr Shell has been a Principal Investigator (PI) on a number of internal and externally funded (including Horizon2020) projects that involve the application of Computational Intelligence (CI) and gaming applications.

The research interests of Dr Shell are focussed around the application of Computational Intelligence, specifically fuzzy logic and transfer learning across and within three main areas: gaming, healthcare and HCI.

He is currently a senior lecturer and researcher in Games and Information Systems at De Montfort University

Research group affiliations

Centre for Computational Intelligence (CCI)

De Montfort University Games And interactive MEdia Research (DMU:GAMER)

Publications and outputs

INNATE: Intelligent Non-invasive Nocturnal epilepsy Assistive TEchnology
Malekmohamadi, H., Shell, J. and Coupland, S., (2016) INNATE: Intelligent Non-invasive Nocturnal epilepsy Assistive TEchnology. In Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV) (p. 351). The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp).
Application of Artificial Neural Network and Support Vector Regression in Cognitive Radio Networks for RF Power Prediction Using Compact Differential Evolution Algorithm
Iliya, S. et al. (2015) Application of Artificial Neural Network and Support Vector Regression in Cognitive Radio Networks for RF Power Prediction Using Compact Differential Evolution Algorithm. 2015 Federated Conference on Computer Science and Information Systems (FedCSIS), pp. 55-66
Optimized Neural Network Using Differential Evolutionary and Swarm Intelligence Optimization Algorithms for RF Power Prediction in Cognitive Radio Network: A Comparative study
Iliya, S. et al. (2014) Optimized Neural Network Using Differential Evolutionary and Swarm Intelligence Optimization Algorithms for RF Power Prediction in Cognitive Radio Network: A Comparative study. 2014 IEEE 6th International Conference On Adaptive Science & Technology (ICAST)
Fuzzy Transfer Learning: Methodology and application
Shell, J. and Coupland, S. (2015)Fuzzy Transfer Learning: Methodology and application. Information Sciences, 293, 1 pp. 59-79
Optimized Artificial Neural Network Using Differential Evolution for Prediction of RF Power in VHF/UHF TV and GSM 900 Bands for Cognitive Radio Networks
Iliya, S. et al. (2014) Optimized Artificial Neural Network Using Differential Evolution for Prediction of RF Power in VHF/UHF TV and GSM 900 Bands for Cognitive Radio Networks. 14th UK Workshop on Computational Intelligence (UKCI), 2014
Logan's run: Lane optimisation using genetic algorithms based on nsga-ii
Witheridge, S., Passow, B.N. and Shell, J., (2014). Logan's run: Lane optimisation using genetic algorithms based on nsga-ii. In Neural Networks (IJCNN), 2014 International Joint Conference on (pp. 63-68). IEEE.
Where Are the Pictures? Linking Photographic Records across Collections Using Fuzzy Logic.
Brown, S., Croft, D. Coupland, S., Shell, J. and von Lünen, A. (2014) Where Are the Pictures? Linking Photographic Records across Collections Using Fuzzy Logic. In: Museums and the Web 2013: Selected Papers from Two International Conferences, N. Proctor & R. Cherry (eds). Silver Spring, MD: Museums and the Web. pp. 117-127
A fast and efficient semantic short text similarity metric
Croft, D., Coupland, S., Shell, J. and Brown, S. (2013) A fast and efficient semantic short text similarity metric. 2013 13th UK Workshop on Computational Intelligence, UKCI 2013, Article number 6651309, pp. 221-227
Fuzzy Transfer Learning
Towards fuzzy transfer learning for intelligent environments
Shell, J. and Coupland, S., (2012) Towards fuzzy transfer learning for intelligent environments. In: International Joint Conference on Ambient Intelligence. Springer Berlin Heidelberg, pp. 145-160

Click here to view a full listing of Jethro Shell's publications and outputs.

Research interests/expertise

Computational intelligence
Computer game AI
Fuzzy logic
Transfer learning
Dynamic content generation
Medical applications of CI
Human computer interface
Sensors
Virtual reality

Areas of teaching

Game design
Mobile games
Fuzzy logic
Games projects
UML
Game AI
Physics

Qualifications

Courses taught

IMAT1606: Game Architecture, Design and Development
IMAT2608: Mobile Games
IMAT2800: Mechanics and Artificial Intelligence For Simulation
IMAT3406: Fuzzy Logic and Knowledge Based Systems
IMAT3451: Computing Project

Externally funded research grants information

3D-TuneIn: H2020 project to produce digital games applied to hearing aids to address social inclusion, 01 June 2015 to 31 May 2018, Principal Investigator (Imperial College, University of Nottingham, Vianet, Reactify, University of Malaga)

Internally funded research project information

INNATE: HEIF Project to detect and predict nocturnal seizures using non-invasive techniques, 6 Jan - 01 June 2016, Principal Investigator.

Professional esteem indicators

IEEE Transactions on Neural Networks and Learning Systems, Jan 2014, current, reviewer
Sensors, March 2014, current, reviewer
IEEE Transactions on Computational Intelligence and AI in Games, Oct 2016, current, reviewer

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