Personal statement

Andy Gray is a Senior Lecturer in Computing and Co-Programme Lead for Computing at Bath Spa University. His work centres on artificial intelligence (AI) and machine learning (ML), with a focus on designing and evaluating systems that support decision-making in both educational and organisational contexts.

He was part of the EPSRC-funded Centre for Doctoral Training in Enhancing Human Interactions and Collaborations with Data and Intelligence-Driven Systems. His research explores how AI can reduce teacher workload, improve the reliability and transparency of assessment, and support the development of more effective learning experiences.

His current research continues to explore the use of AI in educational assessment, student support, and cyber security. He is also involved in AI research in collaboration with government agencies.

Andy is actively involved in academic and professional communities, serving as a committee member for the BCS Bristol and Bath branch, an Expert Board Member for the Comparative Judgement Research Consortium (CJRC), and a Publication Board Member and co-editor for Learning and Innovation.

Before entering higher education, Andy taught computer science in secondary schools and sixth forms across England. This experience informs his research, ensuring it remains grounded in real-world challenges and practical application.

His work addresses the critical challenge of ensuring AI systems are not only effective, but also transparent, trustworthy, and fit for real-world deployment in education and the public sector.

In addition to his academic work, Andy provides consultancy services focused on building and implementing AI solutions. He supports businesses in transitioning to AI adoption, helping them integrate intelligent systems that enhance operational efficiency, decision-making, and innovation.

Academic qualifications

  • PhD in Artificial Intelligence and Machine Learning
  • PGCert in HE practice
  • MSc in Human-centred Big Data and Artificial Intelligence
  • MSc in Advanced Computer Science
  • PGCE in Secondary Computing & ICT
  • BSc in Computing and Information Systems.

Professional memberships

  • BCS (Chartered Institute for IT)
  • ACM (Association for Computing Machinery)
  • Fellow - Higher Education Academy (FHEA)
  • Qualified Teacher Status (QTS).

Other external roles

  • Comparative Judgement Research Consortium (CJRC) Expert Board Member
  • BCS Committee Member for the Bristol and Bath Region – University Liaison Officer
  • Leaning and Innovation Publication Board Member and co-Editor.

Teaching subjects

  • CPU5006-20: Artificial Intelligence (Module Leader)
  • CPU6002-20: Innovation lab I (Module Leader)
  • CPU6003-20: Innovation lab II (Module Leader)
  • CCO4007-20: Web Development (Module Leader).

Areas of Expertise

  • Artificial Intelligence
  • Machine Learning
  • Bayesian Optimisation
  • Education (Secondary, Further Education, Higher Education)
  • Software Engineering
  • Mobile App Development (iOS).

Research Supervision

Andy is interested in supervising students seeking innovative ways to create and use AI or software solutions across many disciplines with a human-first approach.

Areas of interest for research supervision

  • Artificial Intelligence
  • Machine Learning
  • Education
  • Software Engineering
  • Policy and Governance
  • Human-Computer Interaction (HCI).

Current PhD Projects Supervision

  • Human-in-the-Loop Bayesian Comparative Judgment for Real World Large Scale Data (current)
  • A Systems Modelling paradigm for achieving Secure By Design (current).

Research and academic outputs

Go to ResearchSPAce

Using Elo rating as a metric for comparative judgement in educational assessment
book_section

Gray, A, Rahat, A.A.M, Crick, T, Lindsay, S and Wallace, D (2022) 'Using Elo rating as a metric for comparative judgement in educational assessment.' In: ICEMT '22: Proceedings of the 6th International Conference on Education and Multimedia Technology. Association for Computing Machinery, Guangzhou, China, pp. 272-278. ISBN 9781450396455

A Bayesian active learning approach to comparative judgement within education assessment
article

Gray, A, Rahat, A, Crick, T and Lindsay, S (2024) 'A Bayesian active learning approach to comparative judgement within education assessment.' Computers and Education: Artificial Intelligence, 6. e100245. ISSN 2666-920X

A Bayesian active learning approach to comparative judgement within education assessment
conference_item

Gray, A, Rahat, A, Crick, T and Lindsay, S (2025) A Bayesian active learning approach to comparative judgement within education assessment. In: UK AI Research Symposium, 8-9 September 2025, Northumbria University, Newcastle, UK.

Bayesian comparative judgement: a new approach to enhancing accuracy in ranking pairwise comparisons
conference_item

Gray, A, Rahat, A, Crick, T and Lindsay, S (2024) Bayesian comparative judgement: a new approach to enhancing accuracy in ranking pairwise comparisons. In: Royal Statistical Society International Conference, 2-5 September 2024, Brighton, UK.