Staff Profile
Dr Theocharis Kyriacou
Associate Professor of Artificial Intelligence
I joined York St John University in 2025, bringing over two decades of academic and research experience in data science, machine learning, robotics, and computer science education. My academic journey began with a BEng (Hons) in Electronic Engineering (Systems) from the University of Sheffield, followed by a PhD in Computer Science from the University of Plymouth. Before joining York St John, I held senior academic and leadership positions at Keele University, where I served as Reader in Computer Science, Director of Education, and Deputy Head of the School of Computer Science and Mathematics.
My work is characterised by a passion for interdisciplinary innovation, bridging the gap between academic excellence and real-world application. I have led numerous research and enterprise collaborations across sectors such as healthcare, education, automotive, and agriculture, generating over £2 million in external funding in recent years. I am also a Senior Fellow of the Higher Education Academy (SFHEA), reflecting my sustained commitment to advancing learning and teaching practice.
At York St John, my vision is to foster an environment where Artificial Intelligence research and education empower creativity, ethical practice, and innovation. I am deeply committed to mentoring students and colleagues alike, building bridges between academia and industry, and advancing AI as a transformative force for societal benefit.
- School – York Business School
- Email – t.kyriacou@yorksj.ac.uk
Teaching
My teaching philosophy is grounded in the belief that computer science and AI education should inspire curiosity, creativity, and confidence. Over my career, I have designed and delivered a broad range of modules at undergraduate and postgraduate levels, spanning programming fundamentals, mobile application development, data science and machine learning. I place particular emphasis on developing students’ problem-solving and critical-thinking abilities, supported by authentic, industry-relevant experiences.
As programme director and director of education in the past, I led the redesign and expansion of academic portfolios, with the creation of new undergraduate and postgraduate programmes as well as apprenticeship and online programmes. I also developed partnerships with leading employers to co-design data science curricula, enabling apprenticeships and live project opportunities that enhanced employability and student engagement.
My dedication to excellence in education has been recognised through multiple student-led award nominations. As a Senior Fellow of the HEA, I remain committed to championing evidence-based, inclusive, and innovative pedagogy that prepares graduates to thrive in a rapidly evolving digital world.
Research
My research integrates Artificial Intelligence, Machine Learning, and Data Science to address complex, real-world challenges through interdisciplinary collaboration. I have published over 70 peer-reviewed papers and led high-impact projects funded by UKRI and privately by companies. My work applies AI techniques across diverse domains, including health and medicine, biology, education, farming/agri-tech, and industry.
A distinctive feature of my research is its translational focus, turning academic innovation into tangible societal and industrial outcomes. I have successfully led multiple Knowledge Transfer Partnerships (KTPs) and enterprise collaborations with organisations such as Bentley Motors, TMT First, London Stone, and RAFT Solutions. These projects have improved business processes, enhanced data-driven decision-making, and provided rich opportunities for students and researchers to engage with industry.
Beyond research income and outputs, I value collaboration and mentorship. I have supervised multiple PhD and MPhil students to completion and maintain active partnerships with clinical and academic colleagues in the UK and Europe. Looking ahead, my research aims to advance ethical, explainable AI applications that deliver measurable benefit to individuals, institutions, and communities worldwide.
Publications
Journal papers
Agbo, B., Morris, C., Osman, M., Basketts, J. and Kyriacou, T., 2024. A systematic literature review on software applications used to support curriculum development and delivery in primary and secondary education. International Journal of Educational Research Open, 7, 100385.
Matetic, A., Kyriacou, T. and Mamas, M.A., 2024. Machine-learning clustering analysis in novel patients with ST-elevation acute myocardial infarction. International Journal of Cardiology, 411, 132272.
Bentick, K., Runevic, J., Akula, S., Kyriacou, T., Cool, P. and Andras, P., 2023. Machine learning models based on routinely sampled blood tests can predict the presence of malignancy amongst patients with suspected musculoskeletal malignancy. Methods, 220, pp. 55–60.
Jordan, K., Rathod-Mistry, T., van der Windt, D.A., Bailey, J., Chen, Y., Clarson, L., Denaxas, S., Hayward, R.A., Hemingway, H., Kyriacou, T. and Mamas, M.A., 2023. Determining cardiovascular risk in patients with unattributed chest pain in UK primary care: an electronic health record study. European Journal of Preventive Cardiology. 30(11):1151–1161.
Jordan, K., Rathod-Mistry, T., Bailey, J., van der Windt, D., Chen, Y., Clarson, L., Denaxas, S., Hayward, R., Hemingway, H., Kyriacou, T. and Mamas, M., 2022. Prediction of cardiovascular disease in patients with unattributed chest pain in UK primary care. Society for Academic Primary Care (SAPC) Conference, July 2022.
Joseph, G., Orme, R., Kyriacou, T., Fricker, R.A. and Roach, P., 2021. Effects of surface chemistry interaction on primary neural stem cell neurosphere responses. ACS Omega 2021, 6 (30), 19901-19910.
Rukasha, T., Woolley, S.I., Kyriacou, T. and Collins, T., 2020. Evaluation of wearable electronics for epilepsy: A systematic review. Electronics, 9(6), 968.
Philp, F., Al-Shallawi, A., Kyriacou, T., Blana, D. and Pandyan, A.D., 2019. Improving predictor selection for injury modelling methods in male footballers. BMJ Open Sport & Exercise Medicine 2020;6:e000634. doi: 10.1136/bmjsem-2019-000634.
Patterson, K., Kyriacou, T., Desai, M., Carroll, W.D. and Gilchrist, F.J., 2019. Growth from birth to two years in a cohort of children diagnosed with CF by newborn screening. BMC Pediatrics, 19(1), 356.
Wootton, A.J., Butcher, J.B., Kyriacou, T., Day, C.R. and Haycock, P.W., 2017. Structural health monitoring of a footbridge using echo state networks and NARMAX. Engineering Applications of Artificial Intelligence, 64, pp. 152–163.
Patterson, K., Kyriacou, T., Desai, M., Carroll, W.D. and Gilchrist, F.J., 2016. Modelling nutritional outcomes for infants diagnosed with cystic fibrosis by newborn screening. Thorax, 71(3), A131 -A132.
de Quincey, E., Turner, M., Williams, N. and Kyriacou, T., 2016. Learner analytics: The need for user-centred design in learning analytics. EAI Endorsed Transactions on Ambient Systems, 16(9), e8.
Kouzouna, A., Gilchrist, F.J., Ball, V., Kyriacou, T., Henderson, J. and Pandyan, A.D., 2016. A systematic review of early life factors which adversely affect subsequent lung function. Paediatric Respiratory Reviews, Volume 20, September 2016, Pages 67-75.
Blana, D., Kyriacou, T., Lambrecht, J.M. and Chadwick, E.K., 2015. Feasibility of using combined EMG and kinematic signals for prosthesis control: A simulation study using a virtual reality environment. Journal of Electromyography and Kinesiology, 21(1), pp. 21–27.
Major, L., Kyriacou, T. and Brereton, O.P., 2014. The effectiveness of simulated robots for supporting the learning of introductory programming: A multi-case case study. Journal of Computer Science Education, 24(2-3), pp. 193–228.
Stewart, C., Kyriacou, T., Postans, N. and Jarvis, S.E., 2014. Creating non-linear models of human gait. Gait & Posture, 39(1), pp.140–141.
Stewart, C., Kyriacou, T., Chadwick, E. and Jarvis, S., 2014. The potential of using NARMAX for modelling human gait: Creating a polynomial fit of knee flexion from joint moments. European Society for Movement Analysis in Adults and Children (ESMAC), pp.255–255.
Moss, G.P., Kyriacou, T. and Wilkinson, S.C., 2013. The application of Non-Linear Auto-Regressive Moving Average with Exogenous Input (NARMAX) to modelling the absorption across human skin. In: R. Chilcott and K.R. Brain, eds. Advances in Dermatological Sciences. Cambridge: Royal Society of Chemistry. pp.384–390.
Major, L., Kyriacou, T. and Brereton, O.P., 2012. Systematic literature review: Teaching novices programming using robots. IET Software, 6(6), pp.502–513.
Kyriacou, T., 2012. Using an evolutionary algorithm to determine the parameters of a biologically inspired model of head direction cells. Journal of Computational Neuroscience, 32(2), pp.281–295.
Major, L., Kyriacou, T. and Brereton, O.P., 2011. Systematic literature review: Teaching novices programming using robots. Evaluation and Assessment in Software Engineering (EASE 2011), pp.21–30.
Kyriacou, T., 2011. An implementation of a biologically inspired model of head direction cells on a robot. In: Towards Autonomous Robotic Systems (TAROS) 2011. Lecture Notes in Computer Science, vol. 6856, pp. 66–77.
Kyriacou, T., Nehmzow, U., Iglesias, R. and Billings, S.A., 2008. Accurate robot simulation through system identification. Robotics and Autonomous Systems, 56(12), pp.1082–1093.
Akanyeti, O., Kyriacou, T., Nehmzow, U., Iglesias, R. and Billings, S.A., 2007. Visual task identification and characterisation using polynomial models. Robotics and Autonomous Systems, 55(9), pp.711–719.
Nehmzow, U., Kyriacou, T., Iglesias, R. and Billings, S.A., 2007. Task identification and characterisation in mobile robotics through non-linear modelling. Robotics and Autonomous Systems, 55(4), pp.267–275.
Iglesias, R., Nehmzow, U., Kyriacou, T. and Billings, S.A., 2006. Training and analysis of mobile robot behaviour through system identification. In: Current Topics in Artificial Intelligence. 4177. 470-479. 10.1007/11881216_49.
Nehmzow, U., Akanyeti, O., Iglesias, R., Kyriacou, T. and Billings, S.A., 2006. Comparing robot controllers through system identification. In: From Animals to Animats 9. Lecture Notes in Computer Science, vol. 4095, pp. 843–854.
Nehmzow, U., Kyriacou, T., Iglesias, R. and Billings, S.A., 2006. Robot learning through task identification. Robotics and Autonomous Systems, 54(9), pp.766–778.
Kyriacou, T., Nehmzow, U., Iglesias, R. and Billings, S.A., 2005. Task characterisation and cross-platform programming through system identification. Advanced Robotic Systems, 2(3), pp.317–324.
Kyriacou, T., Bugmann, G. and Lauria, S., 2005. Vision-based urban navigation procedures for verbally instructed robots. Robotics and Autonomous Systems, 51(1), pp.69–80.
Lauria, S., Bugmann, G., Kyriacou, T. and Klein, E., 2002. Mobile robot programming using natural language. Robotics and Autonomous Systems, 38(3–4), pp.171–181.
Lauria, S., Bugmann, G., Kyriacou, T., Bos, J. and Klein, E., 2001. Training personal robots using natural language instruction. IEEE Intelligent Systems, 16(5), pp.38–45.
Conferences
Akinyemi, I., Kyriacou, T., Burton, K. and Statham, J., 2025. A Machine Learning Model for Frozen-thawed Bull Semen Quality Assessment, Association of Embryo Technology in Europe (AETE) 2025, Ireland.
Akinyemi, I., Kyriacou, T., Burton, K. and Statham, J., 2024. Application of machine learning for objective bull semen quality assessment. British Cattle Veterinary Association (BCVA) Congress 2024, UK.
Ajibade-Ajibosin, B., Ani, U.D., Turner, M. and Kyriacou, T., 2024. Improving credit card fraud detection with combined feature extraction and class balancing optimisation technique. In: International Conference on Cybersecurity, Situational Awareness and Social Media, Cyber Science 2024. Edinburgh, Scotland, UK.
Lazraq, K., Kyriacou, T. and Gahart, A., 2022. Applied data science in the automotive industry: a customer churn case study. Royal Statistical Society 2022 International Conference, September 2022.
de Quincey, E., Briggs, C., Kyriacou, T. and Waller, R., 2019. Student-centred design of a learning analytics system. In: Proceedings of the 9th International Conference on Learning Analytics & Knowledge (LAK19). pp. 353–362.
Jarvis, D. and Kyriacou, T., 2018. The effect of pose on the distribution of edge gradients in omnidirectional images. In: Towards Autonomous Robotic Systems (TAROS) 2018.
Joseph, G., Fricker, R., Kyriacou, T. and Roach, P., 2016. Machine learning techniques for information surface engineering for in-vitro neural stem cell control. 15th Annual Conference of the UK Society for Biomaterials (UKSB) 2016.
de Quincey, E., Kyriacou, T. and Pantin, T., 2016. #Hayfever; A longitudinal study into hay fever related tweets in the UK. In: Proceedings of the 6th International Conference on Digital Health (DH’16). pp. 85–89.
Major, L., Kyriacou, T. and Brereton, O.P., 2012. Teaching novices programming using a robot simulator: Case study protocol. In: 24th Psychology of Programming Interest Group Annual Conference (PPIG 2012). pp.93–104.
Moss, G.P., Kyriacou, T., Wilkinson, S.C., Judd, A. and Gullick, D.R., 2012. Modelling of absorption across skin and silicone membranes using non-linear auto-regressive moving average with exogenous input (NARMAX) methods. Stratum Corneum VII Conference, 34(4), pp.377–377.
Major, L., Kyriacou, T. and Brereton, O.P., 2011. Experiences of prospective high school teachers using a programming teaching tool. In: 11th Koli Calling International Conference on Computing Education Research (Koli Calling '11). pp.126–131.
Quintía, P., Iglesias, R., Regueiro, C.V., Rodríguez, M. and Kyriacou, T., 2012. Selecting the most relevant sensors in a wall following behaviour. In: XIII Workshop of Physical Agents 2012, pp.57–64.
Kyriacou, T., Butcher, J. and Day, C., 2011. A model of head direction cells with changing preferred head direction. In: 4th International Workshop on Evolutionary and Reinforcement Learning for Autonomous Robot Systems (ERLARS 2011).
Conferences continued
Major, L., Kyriacou, T. and Brereton, O.P., 2011. Simulated robotic agents as tools to teach introductory programming. In: International Technology, Education and Development Conference (INTED 2011), pp.3837–3846.
Kyriacou, T., Iglesias, R., Rodríguez, M. and Quintía, P., 2010. Unsupervised complexity reduction of sensor data for robot learning and adaptation. In: Towards Autonomous Robotic Systems (TAROS 2010), pp.103–110.
Kyriacou, T., Styles, P. and Toon, S., 2008. Robot localization using seismic signals. In: Towards Autonomous Robotic Systems (TAROS 2008), pp.35–42.
Nehmzow, U., Akanyeti, O., Weinrich, C., Kyriacou, T. and Billings, S.A., 2007. Robot programming by demonstration through system identification. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2007), pp.801–806.
Nehmzow, U., Akanyeti, O., Weinrich, C., Kyriacou, T. and Billings, S.A., 2007. Learning by observation through system identification. In: Towards Autonomous Robotic Systems (TAROS 2007), pp.17–24.
Akanyeti, O., Nehmzow, U., Weinrich, C., Kyriacou, T. and Billings, S.A., 2007. Programming mobile robots by demonstration through system identification. In: European Conference on Mobile Robotics (ECMR 2007), pp.162–167.
Iglesias, R., Kyriacou, T., Nehmzow, U. and Billings, S.A., 2006. Route training in mobile robotics through system identification. In: 15th International Conference on Computer and Information Science and Engineering (CISE 2006), pp.181–186.
Kyriacou, T., Akanyeti, O., Nehmzow, U., Iglesias, R. and Billings, S.A., 2006. Visual task identification using polynomial models. In: Towards Autonomous Robotic Systems (TAROS 2006), pp.96–102.
Nehmzow, U., Kyriacou, T., Iglesias, R. and Billings, S.A., 2005. Self-localisation through system identification. In: 2nd European Conference on Mobile Robots (ECMR 2005), pp.14–19.
Iglesias, R., Kyriacou, T., Nehmzow, U. and Billings, S.A., 2005. Robot programming through a combination of manual training and system identification. In: 2nd European Conference on Mobile Robots (ECMR 2005), pp.158–163.
Iglesias, R., Nehmzow, U., Kyriacou, T. and Billings, S.A., 2005. Modelling and characterisation of a mobile robot's operation. In: 11th Conference of the Spanish Association for Artificial Intelligence (CAEPIA 2005).
Kyriacou, T., Nehmzow, U., Iglesias, R. and Billings, S.A., 2005. Cross-platform programming through system identification. In: Towards Autonomous Robotic Systems (TAROS 2005), pp.143–150.
Nehmzow, U., Kyriacou, T., Iglesias, R. and Billings, S.A., 2004. RobotMODIC: Modelling, identification and characterisation of mobile robots. In: Towards Autonomous Robotic Systems (TAROS 2004).
Iglesias, R., Kyriacou, T., Nehmzow, U. and Billings, S.A., 2004. Task identification and characterisation in mobile robotics. In: Towards Autonomous Robotic Systems (TAROS 2004).
Bugmann, G., Klein, E., Lauria, S., Bos, J. and Kyriacou, T., 2004. Corpus-based robotics: A route instruction example. In: 8th International Conference on Intelligent Autonomous Systems (IAS-8), pp.96–103.
Kyriacou, T., Bugmann, G. and Lauria, S., 2003. Vision-based urban navigation procedures for verbally instructed robots. In: Towards Intelligent Mobile Robots (TIMR 2003).
Lauria, S., Bugmann, G., Kyriacou, T., Bos, J. and Klein, E., 2002. Converting natural language route instructions into robot executable procedures. In: IEEE International Workshop on Robot and Human Interactive Communication, pp. 223–228.
Kyriacou, T., Bugmann, G. and Lauria, S., 2002. Vision-based urban navigation procedures for verbally instructed robots. In: IEEE/RSJ International Conference in Intelligent Robots and Systems (IROS 2002), pp.1326–1331.
Robinson, P., Bugmann, G., Kyriacou, T., Culverhouse, P. and Norman, M., 2002. Mirosot: A teaching and learning tool. In: FIRA 2002 Robot World Congress, pp.309–314.
Bugmann, G., Lauria, S., Kyriacou, T., Bos, J. and Klein, E., 2002. Instruction-based learning for mobile robots. In: Conference on Adaptive Computing in Design and Manufacture (ACDM 2002).
Lauria, S., Bugmann, G., Kyriacou, T. and Klein, E., 2001. Instruction-based learning: How to instruct a personal robot to find HAL. In: 9th European Workshop on Learning Robots, pp.15–24.
Bugmann, G., Lauria, S., Kyriacou, T., Bos, J. and Klein, E., 2001. Using verbal instructions for route learning: Instruction analysis. In: Towards Intelligent Mobile Robots (TIMR 2001).
