Staff Details
Position: Lecturer/ Assistant Professor
Email:Chris.Roadknight@mu.ie
Chris Roadknight is currently a Lecturer/Assistant Professor at Maynooth University, Ireland with research interest in agent-based simulation, machine learning and their applications. Prior to the current position, he was Assistant Professor at University of Nottingham Ningbo, China. He has also held research and management positions withing the National Health Service and British Telecom applying simulation and AI technologies to solve challenging real-world problems. He did his PhD at Nottingham Trent University on modelling the impact of complex environmental conditions on agriculture. He has published widely in journals, conferences, and patents with over 1000 citations.
Research Project
Scientific Treatise
Research Projects
1.Optimising Traffic Flow at the Post of Dover 2010-2012 in association and part funded by the Port of Dover and EPSRC
2.Modelling Colorectal Cancer Outcomes. In association with Nottingham University Hospitals
3.Modelling Tanzania Telecoms Traffic 2017. EPSRC (EP/L021080/1)
4.Ningbo Port Modelling. Ningbo Science Technology Bureau, Ref: 2019B10026. 2019/10-2022. PI.
Recent-ish Papers
1.Improving understanding of EEG measurements using transparent machine learning models
C Roadknight, G Zong, P Rattadilok
International Conference on Health Information Science, 134-142
2019
2.Teaching key machine learning principles using anti-learning datasets
C Roadknight, P Rattadilok, U Aickelin
2018 IEEE International Conference on Teaching, Assessment, and Learning
3.Teaching students about machine learning through a gamified approach
P Rattadilok, C Roadknight, L Li
2018 IEEE international conference on teaching, assessment, and learning
4.Improving Student's Engagement Through the Use of Learning Modules, Instantaneous Feedback and Automated Marking
P Rattadilok, C Roadknight
2018 IEEE International Conference on Teaching, Assessment, and Learning
5.An ensemble of machine learning and anti-learning methods for predicting tumour patient survival rates
C Roadknight, D Suryanarayanan, U Aickelin, J Scholefield, L Durrant
2015 IEEE International Conference on Data Science and Advanced Analytics
6.Preliminary experiments with ensembles of neurally diverse artificial neural networks for pattern recognition
A Adamu, T Maul, A Bargiela, C Roadknight
Recent Advances in Information and Communication Technology 2015, 85-96
2015
7.Data classification using the Dempster–Shafer method
Q Chen, A Whitbrook, U Aickelin, C Roadknight
Journal of Experimental & Theoretical Artificial Intelligence 26 (4), 493-517
2014
8.A methodology for automatic classification of breast cancer immunohistochemical data using semi-supervised Fuzzy c-Means
DTC Lai, JM Garibaldi, D Soria, CM Roadknight
Central European Journal of Operations Research 22 (3), 475-499
2014
9.Ensemble learning of colorectal cancer survival rates
C Roadknight, U Aickelin, J Scholefield, L Durrant
2013 IEEE International Conference on Computational Intelligence and Virtual
10.Supervised learning and anti-learning of colorectal cancer classes and survival rates from cellular biology parameters
C Roadknight, U Aickelin, G Qiu, J Scholefield, L Durrant
2012 IEEE International Conference on Systems, Man, and Cybernetics
11.Biomarker clustering of colorectal cancer data to complement clinical classification
C Roadknight, U Aickelin, A Ladas, D Soria, J Scholefield, L Durrant
2012 Federated Conference on Computer Science and Information Systems
12.UNDERSEA SEISMIC SENSING SYSTEM AND METHOD
DJ Heatley, JE Tateson, CM Roadknight, MA Shackleton
EP Patent 1,866,669
2012
13.Validation of a microsimulation of the Port of Dover
C Roadknight, U Aickelin, G Sherman
Journal of Computational Science 3 (1-2), 56-66 12
2012
14.Nodal policy inclusive techniques for operating an ad hoc network
CM Roadknight
US Patent 8,031,684
2011
15.Sensing system
DJT Heatley, JE Tateson, CM Roadknight, MA Shackleton
US Patent 7,755,971
2010
