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Biography Dr Kyle Martin is a lecturer working in the AIR research group in the RGU School of Computing. During Kyle's PhD, he partnered with British Telecommunications, his work targeted the development of a case-based reasoning engineer support system. A particular focus in this project is the ability to explain the decision-making process and recommendations of the system so that engineers can utilise this information effectively. This has resulted in several publications regarding explainability of deep architectures. Kyle completed his PhD in 2021, after having been hired as a full-time lecturer and researcher in 2019.

Since then, Kyle has been involved with a number of applied machine learning projects across several sectors and industrial partner. This has included projects in digital health (with partners Jiva and Walk With Path), fintech (Sticklr) and horizon scanning (Citizen Advice Scotland). Explainability has remained a key focus in his work, and he is currently co-investigator on the iSee project as part of a European consortium. Through iSee, the consortium hope to use explanation experiences to shape how machine learning is practically explained.

Kyle is an active contributor to both national and international research communities. His work has been published in a mix of conferences and journals. Beyond this, he has acted a programme committee member for both ICCBR and SGAI conferences. Additionally, he has chaired a series of international workshops focussed on Case-Based Reasoning and Deep Learning. Kyle also acted as local organiser and chaired a session of the SICSA Reasoning, Learning and Explainability (ReaLX) workshop, the proceedings of which were published online.
Research Interests Case-Based Reasoning
Deep Metric Learning
ResearcherID KBQ-5507-2024