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The Artificial Intelligence Modelling Lab (AIML) engages in a range of theoretical and applied research in Artificial Intelligence (AI) and Machine Learning (ML). Particular areas of interest include interactive theorem proving, formal modelling and verification, machine learning and its combination with higher level symbolic reasoning, as well as its application to healthcare and other complex, real-world domains.

Some of our Existing and Past External Engagements
Recent Events

During this talk, I report on progress we have made towards formalising Algebraic Quantum Field Theory (AQFT) and present formalisations in the theories of manifolds, Lie groups, and involutive algebras. I will outline a plan to quickly obtain a minimal formalisation of AQFT, suitable for the study of theorems with physical interpretation.
Speaker: Richard Schmoetten

This presentation will presentan assessment of the feasibility of predicting brain health outcomes from sleep duration derived using accelerometery data from UK Biobank.
Speaker: Matt Whelan

In this talk, we describe our investigation of associations between physical multimorbidity and subsequent depression by performing clustering analysis upon baseline morbidity data for UK Biobank participants and then performing survival analysis to compare time to subsequent depression diagnosis.
Speaker: Lauren DeLong