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.
News
-
Special Issue on Mathematics in Artificial Intelligence
19th October 2023
-
Paper on conformance checking over probabilistic events accepted at HICSS-57
18th August 2023
-
Pre-print on Associations between Morbidities in Small But Important Subgroup using a Bayesian approach
8th August 2023
-
Paper on brain tumour survival predictions accepted in Computer Methods and Programs in Biomedicine
15th May 2023
-
Survey pre-print on Neurosymbolic AI for Reasoning on Graph Structures is out on arXiv
15th February 2023
Some of our Existing and Past External Engagements

Recent Events
Integrating Knowledge Graph Data with Large Language Models for Explainable Inference
Researchers have proposed various approaches, including the use of Deep Learning for complex queries on Knowledge Graphs (KGs) and Augmented Language Models that integrate recognition of entities from a KG. In this work, we propose to modify and combine these approaches with recent LLM developments, creating an explainable way for LLMs to work with data from any KG.
Speaker: Carlos Efraín Quintero Narvaez
A joint workshop between FHAIVE (Finland) and AIML where we will explore some of the applications of AI in the biomedical domain.
Exploring AI Based Approaches for Post-operative Microvascular Free Flap Monitoring
I will discuss my PhD project, which aims to explore AI-based approaches for the postoperative monitoring of microvascular free flaps that are as effective and accurate as clinical assessment at identifying compromised free flaps but which are less subjective.
Speaker: Fiona Smith