Professor Kevin Swingler

Professor

Computing Science University of Stirling, Stirling, FK9 4LA

Professor Kevin Swingler

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About me

I am a senior lecturer and head of the division of Computing Science and Mathematics. My field of interest is artificial intelligence (AI), particularly data science, machine learning and computer vision.

Before coming to academia, I ran a software company which developed and sold neural network based software to customers in banking, insurance, marketing and sales.

I like to be innovative in teaching, and I'm expanding the ways we deliver knowledge and skills, including graduate apprenticeships, online degrees, micro-credits and overseas provision.

My research is mostly concerned with applying data science and AI to applications in health and wellbeing. My main research project is developing assistive technologies for the blind using computer vision. I've also worked on projects designed to optimise treatments, predict symptoms and manage scarce resources.

I also run a spin-out company for the University, which provides hardware and consultancy for data collection and analytics.

Research (8)

The main focus of my current research is a project called the Artificial Intelligence Sight Loss Assistant (AISLA). We are using computer vision, machine learning, natural language understanding and other AI tools to develop a system to help people with sight loss to live more independently. The project addresses many challenges in modern AI, as well as being potentially useful to many people.

The project web page is at https://www.aisla.org.uk/. I am keen to collaborate with other researchers with a similar interest as well as with charities and other organisations that help people with sight loss.

Projects

PRISMA reporting guideline and standards for qualitative evidence synthesis
PI: Professor Emma France
Funded by: Medical Research Council

Digital Nutrition Assessment Tool
PI: Dr Jenni Connelly
Funded by: Economic and Social Research Council

INtelligent FOod Recognition and Monitoring for patient wellbeing
PI:
Funded by: Falcon Foodservice Equipment

Food recognition with computer vision
PI:
Funded by: Falcon Foodservice Equipment

Developing meta-ethnography reporting guidelines and standards for research (eMERGE)
PI: Professor Emma France
Funded by: National Institute for Health Research

Knowledge Transfer Partnership between University of Stirling and The Royal College of Midwives
PI:
Funded by: Royal College of Midwives and Technology Strategy Board

Knowledge Transfer Partnership between University of Stirling & ThinkAnalytics Limited
PI: Professor Kevin Swingler
Funded by: Technology Strategy Board and ThinkAnalytics Ltd

The Electronic Sales Engine - An artificial Intelligence based sales optimization system
PI: Professor Kevin Swingler
Funded by: Scottish Enterprise

Outputs (36)

Outputs

Swingler K, Rumble T, Goutcher R, Hibbard P, Donoghue M & Harvey D (2024) Combined Depth and Semantic Segmentation from Synthetic Data and a W-Net Architecture. In: volume 1. 16th International Conference on Neural Computation Theory and Applications, Porto, Portugal, 20.11.2024-22.11.2024. SCITEPRESS - Science and Technology Publications, pp. 413-422. https://doi.org/10.5220/0012877500003837


Conference Paper (published)

Swingler K (2022) A Suite of Incremental Image Degradation Operators for Testing Image Classification Algorithms. In: Back T, van Stein B, Wagner C, Garibaldi J, Lam HK, Cottrell M, Doctor F, Filipe J, Warwick K & Kacprzyk J (eds.) 14th International Conference on Neural Computation Theory and Applications, Valletta, Malta, 24.10.2022-26.10.2022. Setubal, Portugal: SCITEPRESS - Science and Technology Publications, pp. 262-272. https://doi.org/10.5220/0011511000003332


Conference Paper (published)

Swingler K & Grigson C (2022) A Haptic Interface for Guiding People with Visual Impairment using Three Dimensional Computer Vision. In: Back T, van Stein B, Wagner C, Garibaldi J, Lam HK, Cottrell M, Doctor F, Filipe J, Warwick K & Kaprzyk J (eds.) Proceedings of the 14th International Joint Conference on Computational Intelligence (IJCCI 2022) - NCTA. 14th International Conference on Neural Computation Theory and Applications, Valletta, Malta, 24.10.2022-26.10.2022. Setubal, Portugal: SCITEPRESS - Science and Technology Publications, pp. 315-322. https://doi.org/10.5220/0011307800003332


Conference Paper (published)

Swingler K & Bath M (2020) Learning Spatial Relations with a Standard Convolutional Neural Network. In: Merelo JJ, Garibaldi J, Wagner C, Bäck T, Madani K & Warwick K (eds.) Proceedings of the 12th International Joint Conference on Computational Intelligence - Volume 1: NCTA. 12th International Conference on Neural Computation Theory and Applications, Budapest, Hungary, 02.11.2020-04.11.2020. Setubal, Portugal: SCITEPRESS - Science and Technology Publications, pp. 464-470. https://doi.org/10.5220/0010170204640470


Conference Paper (published)

Alqarafi A, Adeel A, Hawalah A, Swingler K & Hussain A (2018) A Semi-supervised Corpus Annotation for Saudi Sentiment Analysis Using Twitter. In: Hussain A, Zhao H, Ren J, Zheng J, Liu C, Luo B & Zhao X (eds.) Advances in Brain Inspired Cognitive Systems. Lecture Notes in Computer Science, 10989. BICS 2018: 9th International Conference on Brain Inspired Cognitive Systems, Xi'an, China, 07.07.2018-08.07.2018. Cham, Switzerland: Springer International Publishing, pp. 589-596. https://doi.org/10.1007/978-3-030-00563-4_57


Conference Paper (published)

Swingler K (2017) High capacity content addressable memory with mixed order hyper networks. In: Merelo J, Rosa A, Cadenas J, Correia A, Mandani K, Ruano A & Filipe J (eds.) Computational Intelligence: International Joint Conference, IJCCI 2015 Lisbon, Portugal, November 12-14, 2015, Revised Selected Papers. Studies in Computational Intelligence, 669. Computational Intelligence International Joint Conference, IJCCI 2015, Lisbon, Portugal, 12.11.2015-14.11.2015. Cham, Switzerland: Springer, pp. 337-358. https://doi.org/10.1007/978-3-319-48506-5_17


Conference Paper (published)

Swingler K (2016) Opening the Black Box: Analysing MLP Functionality Using Walsh Functions. In: Merelo J, Rosa A, Cadenas J, Dourado A, Madani K & Filipe J (eds.) Computational Intelligence. Studies in Computational Intelligence, 620. International Joint Conference on Computational Intelligence (IJCCI) 2014, Rome, Italy, 22.10.2014-24.10.2014. Cham, Switzerland: Springer, pp. 303-323. https://doi.org/10.1007/978-3-319-26393-9_18


Conference Paper (published)

Swingler K (2015) A Comparison of Learning Rules for Mixed Order Hyper Networks. In: Proceedings of the 7th International Joint Conference on Computational Intelligence. NCTA (IJCCI). Setubal, Portugal: Science and Technology Publications, pp. 17-27. http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220%2f0005588000170027; https://doi.org/10.5220/0005588000170027


Conference Paper (published)

Swingler K & Smith L (2014) An analysis of the local optima storage capacity of Hopfield network based fitness function models. In: Nguyen N, Kowalczyk R, Fred A & Joaquim F (eds.) Transactions on Computational Collective Intelligence XVII. Lecture Notes in Computer Science, 8790. Berlin Heidelberg: Springer, pp. 248-271. http://link.springer.com/chapter/10.1007/978-3-662-44994-3_13; https://doi.org/10.1007/978-3-662-44994-3_13


Conference Paper (published)

Swingler K (2014) A walsh analysis of multilayer perceptron function. In: Proceedings of the International Conference on Neural Computation Theory and Applications (IJCCI 2014). NCTA 2014: 6th International Conference on Neural Computation Theory and Applications, Rome, Italy, 22.10.2014-24.10.2014. Setubal, Portugal: Science and Technology Publications, pp. 5-14. http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0004974800050014; https://doi.org/10.5220/0004974800050014


Website Content

Swingler K, Duncan E & Murray J (2013) CARE Measure. 2013. http://www.caremeasure.org/


Conference Paper (published)

Swingler K & Smith L (2013) Mixed order associative networks for function approximation, optimisation and sampling. In: ESANN 2013 proceedings, 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013, Bruges, Belgium, 24.04.2013-26.04.2013. ESANN, pp. 23-28. http://www.i6doc.com/en/livre/?GCOI=28001100131010


Conference Paper (published)

Swingler K (2012) On the Capacity of Hopfield Neural Networks as EDAs for Solving Combinatorial Optimisation Problems. In: Rosa A, Correia A, Madani K, Filipe J & Kacprzyk J (eds.) IJCCI 2012 - Proceedings of the 4th International Joint Conference on Computational Intelligence. 4th International Conference on Evolutionary Computation Theory and Applications, ECTA 2012, and the 4th International Joint Conference on Computational Intelligence, IJCCI 2012, Barcelona, Spain, 05.10.2012-07.10.2012. SciTePress, pp. 152-157.


Conference Paper (published)

Swingler K (2011) The Perils of Ignoring Data Suitability: The Suitability of Data Used to Train Neural Networks Deserves More Attention. In: NCTA 2011 - International Conference on Neural Computation Theory and Application. International Conference on Neural Computation Theory and Application, Paris, France, 24.10.2011-26.10.2011. SciTePress Digital Library. http://www.ncta.ijcci.org/Abstracts/2011/NCTA_2011_Abstracts.htm


Conference Paper (published)

Godley PM, Cairns D, Cowie J, McCall J & Swingler K (2008) The Effects of Mutation and Directed Intervention Crossover When Applied to Scheduling Chemotherapy. In: Keijzer M (ed.) Proceedings of the 10th annual conference on Genetic and evolutionary computation (GECCO). ACM Genetic and Evolutionary Computation Conference (GECCO) 2008, Atlanta, Georgia, 12.07.2008-16.07.2008. New York, USA: Association for Computing Machinery (ACM), pp. 1105-1106. http://portal.acm.org/toc.cfm?id=1389095&type=proceeding&coll=GUIDE&dl=GUIDE&CFID=47644191&CFTOKEN=12932833; https://doi.org/10.1145/1389095.1389300


Conference Paper (published)

Cowie J, Swingler K, Leadbetter C, Maguire R, McCall K & Kearney N (2008) ASYMS-SERAT: A Side-Effect Risk Assessment Tool to Predict Chemotherapy Related Toxicity in Patients with Cancer Receiving Chemotherapy. In: Azevedo L & Londral AR (eds.) Proceedings of the First International Conference on Health Informatics, HEALTHINF 2008, Funchal, Madeira, Portugal, January 28-31, 2008, Volume 2. HEALTHINF - International Conference on Health Informatics 2008, Madeira, Portugal, 28.01.2008-31.01.2008. Setubal, Portugal: INSTICC - Institute for Systems and Technologies of Information, Control and Communication, pp. 225-230. http://www.healthinf.biostec.org/Healthinf2008/


Article

Lukaszewski RA, Yates AM, Jackson MC, Swingler K, Scherer JM, Simpson AJH, Sadler P, McQuillan P, Titball RW, Brooks TJG & Pearce MJ (2008) Presymptomatic Prediction of Sepsis in Intensive Care Unit Patients. Clinical and Vaccine Immunology, 15 (7), pp. 1089-1094. http://cdli.asm.org/cgi/content/abstract/15/7/1089; https://doi.org/10.1128/CVI.00486-07


Conference Paper (published)

Swingler K & Smith L (1995) From steering to alertness: non-intrusive driver monitoring. In: Proceedings of ICANN 95 (Industrial applications). ICANN 95: Neural Networks and their Applications (Industrial applications), Paris, France, 09.10.1995-13.10.1995. Lausanne, Switzerland: European Neural Network Society.


Conference Paper (published)

Smith L & Swingler K (1993) The Filtered Activation Networks. In: ESANN 93: European Symposium on Artificial Neural Networks, Brussels, April 7-8-9, 1993. ESANN ' 93: European Symposium on Artificial Neural Networks, Brussels, 07.04.1993-09.04.1993. Brussels: D Facto Conference Services, pp. 165-170. https://groups.google.com/forum/#!msg/comp.ai.neural-nets/7RWb4AY14W0/cQxvTB1bRJkJ


Teaching

I teach on a number of MSc. modules including databases, Python scripting and data analytics. I also develop material for the online masters programmes that we run.

I have an open door policy for students and I'm happy to help them with any aspect of their learning.

I believe in broad access to university level education, and that non-traditional courses like online degrees, graduate apprenticeships and micro credentials are really important.

Research programmes

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