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 domains.
- Fully Funded PhD: Monitoring daily living to predict health outcomes
- Callum Abbott’s MSc thesis comes top of MSc in Statistics with Data Science
- Programme Co-ordinator post available on Artificial Intelligence for Multiple Long-Term Conditions Programme
- Mechanisation of Minkowski Spacetime released on the Archive of Formal Proof
- Richard Schmoetten recipient of AFR Grant for his PhD
Some of our External Engagement
In this preliminary round of the AI Modelling Lab’s 3-minute thesis/project competition, a first batch of speakers will give us an exciting overview of their research with the help of a single slide. The topics range from healthcare to formalised mathematics, covering both knowledge/symbolic- and data-driven AI.
Speakers: Imogen Morris, Adarsh Prabhakaran,Jorge Gaete-Villegas, Jiawei Zheng, Zonglin Ji, Ramon Mir Fernández
In this talk I will present the use of the Stochastic Block Model (SBM) as an alternative to clustering techniques to study the impact of multimorbidity in in-hospital sepsis and mortality.
Speaker: Jorge Gaete Villegas
We are planning to hold a 3 minute thesis competition within the AIML lab In brief: you have 3 minutes and 1 slide to present your thesis at an accessible level. On Friday I will give a brief description of the competition.
Speaker: Imogen Morris